--- title: "univariate logistic regression reworked" output: html_document --- Univariate logistic regression to examine the relationship between positivity in ELISAs and serological and clinical manifestations of SLE-disease, taking the serological measures as predictors and the presence of different disease-features as dependent variable - Disease-activity Features (SLEDAI): Evaluated at the time of blood collection - different Items of ACR-Criteria: evaluated at entry into the study or symptom onset; usually not subsequently documented create data.frame for export of Odds Ratios and Confidence Intervals in .txt file (to make forest plots with prism) 99% CI Intervals were taken into consideration, but intervals have not been adjusted for multiplicity in the final analysis ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` ```{r} #setwd("Z:/Kleer/Project Paper/Masterfiles/4. Testfiles/") #setwd("/Volumes/KLIM$/Kleer/Project Paper/Masterfiles/4. Testfiles") setwd("/Volumes/KLIM$/Kleer/Project Paper/Submission/DRYAD") getwd() ``` ```{r, read in data} data <- read.csv2("MASTERFILE_kleer_20210305.csv") ``` ```{r create SLE Subset} #creating SLE subset group for logistic regression SLEsubset <- data[1:378, 1:256] ``` ```{r Definition of active Disease} #Definition of active Lupus-Diseaes (-> binary Outcome) as PGA (physicians global assesment) >=1 and SLEDAI-Score >= 6 # PGA: 0=inactive, 1=moderate, 2= active, 3= very active SLEsubset$PGA <- factor(SLEsubset$PGA,levels = c("inactive","moderat", "active", "very active"), labels = c(0,1,2,3)) SLEsubset$PGA <- as.numeric(SLEsubset$PGA) #SLEsubset$PGA #1=inactive, 2=moderate, 3= active, 4= very active # activity defined as PGA >= 1 (>=moderate) & SLEDAI >= 6 SLEsubset$activity <- ifelse(SLEsubset$SELENA>=6 & SLEsubset$PGA >=2, yes=1,no=0) #because 2=moderate #SLEsubset$activity_1 <- factor(SLEsubset$activity_1, levels = c(0,1), #labels=c("inactive", "active")) table(SLEsubset$activity) table (SLEsubset$PGA) ``` ```{r skin involvement (SLEDAI)} SLEsubset$skin_involvement <- ifelse(SLEsubset$MAL == 1 | #Malar rash SLEsubset$APH == 1| #Mucosal ulcers SLEsubset$ALO == 1, yes = 1, no= 0) #Alopecia table(SLEsubset$skin_involvement, useNA = "ifany") ``` ```{r Pleuritis or Pericarditis (SLEDAI)} SLEsubset$PLEPER <- ifelse(SLEsubset$PER ==1 | SLEsubset$PLE == 1, yes = 1, no= 0) table(SLEsubset$PLEPER, useNA = "ifany") ``` ```{r CNS involvement (SLEDAI)} SLEsubset$CNSinvolvement <- ifelse(SLEsubset$PSY ==1 | #Psychosis SLEsubset$SEI ==1 | #Seizures SLEsubset$OBD ==1 #organic Brain Syndrome, , yes = 1, no=0) table(SLEsubset$CNSinvolvement, useNA = "ifany") ``` ```{r Anemia} SLEsubset$Anemia <- ifelse(SLEsubset$sex == "Female" & SLEsubset$HGB < 120, yes= 1, no = ifelse(SLEsubset$sex == "Male" & SLEsubset$HGB < 130, yes=1, no=0)) table(SLEsubset$Anemia) ``` ```{r ESR} SLEsubset$ESRelevated <- ifelse(SLEsubset$sex == "Female" & SLEsubset$Age <= 50 & SLEsubset$ESR > 20, yes=1, no = ifelse(SLEsubset== "Female" & SLEsubset$Age > 50 & SLEsubset$ESR > 30, yes=1, no = ifelse(SLEsubset$sex == "Male" & SLEsubset$Age <=50 & SLEsubset$ESR > 15, yes=1, no = ifelse(SLEsubset$sex == "Male" & SLEsubset$Age > 50 & SLEsubset$ESR > 20, yes= 1, no= 0 )))) ``` ```{r anti-phospholipid-Ab} SLEsubset$APA[SLEsubset$APA == "Present"] <- 1 SLEsubset$APA[SLEsubset$APA == "Absent"] <- 0 SLEsubset$APA[SLEsubset$APA == 99] <- NA SLEsubset$APA <- as.numeric(SLEsubset$APA) table(SLEsubset$APA, useNA = "ifany") ``` ```{r ACR Pleuritis or Pericarditis} SLEsubset$ACR_PLEPER <- ifelse(SLEsubset$A6a ==1 | SLEsubset$A6b ==1, yes=1, no=0) ``` ```{r ACR neurologic disorder} SLEsubset$ACR_neurologic_disorder <- ifelse(SLEsubset$A8a ==1 | SLEsubset$A8b ==1, yes=1, no= 0) ``` ```{r} SLEsubset$ACR_immunologic_disorder <- ifelse(SLEsubset$A10a == 1| SLEsubset$A10b == 1 | SLEsubset$A10c == 1, yes = 1, no = 0) table(SLEsubset$ACR_immunologic_disorder, useNA = "ifany") ``` adding Categorical predictors (Cutoffs) to data.frame "data" as well as data.frame "SLEsubset" ```{r Cutoff anti C1q: 60 reIU} #in data.frame "data" data$AntiC1qpos. <- ifelse(data$antiC1q >60, yes=1, no=0) #numerical vector #as factor: Levels: no yes #data$AntiC1qpos. <- factor(data$AntiC1qpos., #levels=c(0,1), #labels=c("no", "yes")) prop.table(table(data$Group, data$AntiC1qpos.), margin = 1) #in data.frame "SLEsubset" SLEsubset$AntiC1qpos. <- ifelse(SLEsubset$antiC1q >60, yes=1, no=0) #numerical vector #as factor: Levels: no yes #SLEsubset$AntiC1qpos. <- factor(SLEsubset$AntiC1qpos., #levels=c(0,1), #labels=c("no", "yes")) #summary(SLEsubset$AntiC1qpos.) ``` ```{r Cutoff A15: 160 reIU} #A15 former called A08 #data.frame: "data" data$A08pos. <- ifelse(data$A08 >160, yes=1, no=0)#numerical vector #as factor: Levels: no yes #data$A08pos. <- factor(data$A08pos., #levels=c(0,1), #labels=c("no", "yes")) prop.table(table(data$Group, data$A08pos.), margin = 1) #data.frame: "SLEsubset" SLEsubset$A08pos. <- ifelse(SLEsubset$A08 >160, yes=1, no=0)#numerical vector #as factor: Levels: no yes #SLEsubset$A08pos. <- factor(SLEsubset$A08pos., #levels=c(0,1), #labels=c("no", "yes")) ``` ```{r Cutoff A09: 100 reIU} #A09 former called A08shift #data.frame: "data" data$A08shiftpos. <- ifelse(data$A08shift>100, yes=1, no=0)#numerical vector #as factor: Levels: no yes #data$A08shiftpos. <- factor(data$A08shiftpos., #levels=c(0,1), # labels=c("no", "yes")) prop.table(table(data$Group, data$A08shiftpos.), margin = 1) #data.frame: "SLEsubset" SLEsubset$A08shiftpos. <- ifelse(SLEsubset$A08shift>100, yes=1, no=0)#numerical vector #as factor: Levels: no yes #SLEsubset$A08shiftpos. <- factor(SLEsubset$A08shiftpos., #levels=c(0,1), #labels=c("no", "yes")) ``` ```{r Cutoff A86: 425 reIU} #A86 former called A90 #data.frame: "data" data$A90pos. <- ifelse(data$A90>425, yes=1, no=0)#numerical vector #as factor: Levels: no yes #data$A90pos. <- factor(data$A90pos., #levels=c(0,1), #labels=c("no", "yes")) prop.table(table(data$Group, data$A90pos.), margin = 1) #data.frame: "SLEsubset" SLEsubset$A90pos. <- ifelse(SLEsubset$A90>425, yes=1, no=0)#numerical vector #as factor: Levels: no yes #SLEsubset$A90pos. <- factor(SLEsubset$A90pos., #levels=c(0,1), #labels=c("no", "yes")) ``` ```{r Cutoff B41: 50 reIU} #data.frame: "data" data$B41pos. <- ifelse(data$B41>50, yes=1, no=0)#numerical vector #as factor: Levels: no yes #data$B41pos. <- factor(data$B41pos., #levels=c(0,1), #labels=c("no", "yes")) prop.table(table(data$Group, data$B41pos.), margin = 1) #data.frame: "SLEsubset" SLEsubset$B41pos. <- ifelse(SLEsubset$B41>50, yes=1, no=0)#numerical vector #as factor: Levels: no yes #SLEsubset$B41pos. <- factor(SLEsubset$B41pos., #levels=c(0,1), #labels=c("no", "yes")) ``` ```{r Cutoff B43: 25reIU} data$B43pos. <- ifelse(data$B43>25, yes=1, no=0)#numerical vector #as factor: Levels: no yes #data$B43pos. <- factor(data$B43pos., #levels=c(0,1), #labels=c("no", "yes")) prop.table(table(data$Group, data$B43pos.), margin = 1) #data.frame: "SLEsubset" SLEsubset$B43pos. <- ifelse(SLEsubset$B43>25, yes=1, no=0)#numerical vector #as factor: Levels: no yes #SLEsubset$B43pos. <- factor(SLEsubset$B43pos., #levels=c(0,1), #labels=c("no", "yes")) ``` ```{r Cutoff B83: 51 reIU} data$B83pos. <- ifelse(data$B83>51, yes=1, no=0)#numerical vector #as factor: Levels: no yes #data$B83pos. <- factor(data$B83pos., #levels=c(0,1), #labels=c("no", "yes")) prop.table(table(data$Group, data$B83pos.), margin = 1) #data.frame: "SLEsubset" SLEsubset$B83pos. <- ifelse(SLEsubset$B83>51, yes=1, no=0)#numerical vector #as factor: Levels: no yes #SLEsubset$B83pos. <- factor(SLEsubset$B83pos., #levels=c(0,1), #labels=c("no", "yes")) ``` ```{r univariate logistic regression AntiC1q} #create data.frame for export of Odds Ratios and Confidence Intervals in .txt file (to create forest plots with prism) mycol <- c("mycol", "myCIlow", "myOdd", "myCIup") data.frame_AntiC1q_95 <- data.frame(colum_name = mycol) #95% Confidence-Intervals data.frame_AntiC1q_99 <- data.frame(colum_name = mycol) #99% Confidence Intervals #activity logistic_active_AntiC1q<-glm(activity ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_active_AntiC1q # x =temporary variable data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Fever logistic_Fever_AntiC1q<- glm(FEV ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_Fever_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Fever', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Fever', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Arthritis logistic_ARI_AntiC1q <-glm(ARI ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_ARI_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #skin involvement logistic_skin_AntiC1q<-glm(skin_involvement ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_skin_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('skin involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('skin involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Vasculitis logistic_EVA_AntiC1q <-glm(EVA ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_EVA_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Vasculitis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Vasculitis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Pleuritis or Pericarditis logistic_PLEPER_AntiC1q <-glm(PLEPER ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_PLEPER_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Cerebrovascular accident #table(SLEsubset$STR) #Patients with Stroke: 4/378 #leaving Stroke out in analysis due to too small sample size #logistic_STR_AntiC1q <-glm(STR ~ AntiC1qpos., data = SLEsubset, family = "binomial") #x <- logistic_STR_AntiC1q #data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Cerebrovascular accident', #exp(confint(x)[2,1]), #exp(x$coefficients[2]), #exp(confint(x)[2,2]))) #data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Cerebrovascular accident', #exp(confint(x, level = 0.99)[2,1]), #exp(x$coefficients[2]), #exp(confint(x, level = 0.99)[2,2]))) #CNS involvement logistic_CNS_AntiC1q <-glm(CNSinvolvement ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_CNS_AntiC1q round(exp(x$coefficients),3) round(exp(confint(x)),3) round(exp(confint(x, level=0.99)),4) data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('CNS involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('CNS involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Leucopenia logistic_LEU_AntiC1q<-glm(LEU ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_LEU_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Leucopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Leucopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Thrombocytopenia logistic_PLA_AntiC1q<-glm(PLA ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_PLA_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Thrombocytopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Thrombocytopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Proteinuria logistic_Prot_AntiC1q<-glm(PRO ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_Prot_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Proteinuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Proteinuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Haematuria logistic_HUM_AntiC1q <-glm(HUM ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_HUM_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Haematuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Haematuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #low Complement logistic_TCO_AntiC1q <-glm(TCO ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_TCO_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('low Complement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('low Complement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #anti-ds-DNA logistic_DNA_AntiC1q <-glm(DNA ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logistic_DNA_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('anti-ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('anti-ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Anemia logi_Anemia_AntiC1q <-glm(Anemia ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logi_Anemia_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Anemia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Anemia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Ery sedimention rate logi_ESRelevated_AntiC1q <-glm(ESRelevated ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logi_ESRelevated_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('ESR elevated', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('ESR elevated', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Antiphospholipid Antibodies logi_APA_AntiC1q <- glm(APA ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logi_APA_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Antiphospholipid Antibodies', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Antiphospholipid Antibodies', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$1 Malar rash logi_ACR_Malar_rash_AntiC1q <- glm(A1 ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Malar_rash_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Malar rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Malar rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$2 Discoid rash logi_ACR_Discoid_rash_AntiC1q <- glm(A2 ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Discoid_rash_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Discoid rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Discoid rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$3 Photosensitivity logi_ACR_Photosensitivity_AntiC1q <- glm(A3 ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Photosensitivity_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Photosensitivity', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Photosensitivity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$4 Nasopharyngeal ulcers logi_ACR_Nasopharyngeal_ulcers_AntiC1q <- glm(A4 ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Nasopharyngeal_ulcers_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Nasopharyngeal ulcers', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Nasopharyngeal ulcers', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$5 Arthritis logi_ACR_Arthritis_AntiC1q <- glm(A5 ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Arthritis_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$6 Pleuritis or Pericarditis logi_ACR_PLEPER_AntiC1q <- glm(ACR_PLEPER ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_PLEPER_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$7 renal Disorder logi_ACR_renal_Disorder_AntiC1q <- glm(A7 ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_renal_Disorder_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('renal Disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('renal Disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$8 neurologic disorder logi_ACR_neuro_AntiC1q <- glm(ACR_neurologic_disorder ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <-logi_ACR_neuro_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('neurologic disorder ', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('neurologic disorder ', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$9 Haematologic disorder logi_ACR_Haematologic_Disorder_AntiC1q <- glm(A9 ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Haematologic_Disorder_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Haematologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Haematologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$10 Immunologic disorder logi_ACR_immunologic_AntiC1q <- glm(ACR_immunologic_disorder ~ AntiC1qpos., data = SLEsubset, family = "binomial") x <- logi_ACR_immunologic_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Immunologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Immunologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti ds-DNA logi_ACR_DNA_AntiC1q <- glm(A10a ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_DNA_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti-Sm logi_ACR_sm_AntiC1q <- glm(A10b ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_sm_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('anti-Sm', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('anti-Sm', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_Anti-Phospholipid logi_ACR_APL_AntiC1q <- glm(A10c ~ AntiC1qpos., data=SLEsubset, family = "binomial") x <- logi_ACR_APL_AntiC1q data.frame_AntiC1q_95 <- cbind(data.frame_AntiC1q_95, c('Anti-Phospholipid', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_AntiC1q_99 <- cbind(data.frame_AntiC1q_99, c('Anti-Phospholipid', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) ``` ```{r} data.frame_AntiC1q_95 <- data.frame_AntiC1q_95 [ , c(1,seq.int(30,2))] data.frame_AntiC1q_99 <- data.frame_AntiC1q_99 [ , c(1,seq.int(30,2))] ``` ```{r} #re-organising data.frames for export in .txt-file names(data.frame_AntiC1q_95) <- as.matrix(data.frame_AntiC1q_95[1,]) data.frame_AntiC1q_95 <- data.frame_AntiC1q_95[-1, ] data.frame_AntiC1q_95[] <- lapply(data.frame_AntiC1q_95, function(x) type.convert(as.character(x))) data.frame_AntiC1q_95 data.frame_AntiC1q_95$mycol <-NULL data.frame_AntiC1q_95 <- round(data.frame_AntiC1q_95,3) names(data.frame_AntiC1q_99) <- as.matrix(data.frame_AntiC1q_99[1,]) data.frame_AntiC1q_99 <- data.frame_AntiC1q_99[-1, ] data.frame_AntiC1q_99[] <- lapply(data.frame_AntiC1q_99, function(x) type.convert(as.character(x))) data.frame_AntiC1q_99 data.frame_AntiC1q_99$mycol <-NULL data.frame_AntiC1q_99 <-round(data.frame_AntiC1q_99,3) ``` ```{r} # Write a new File with tabstops as sep and no Col and Row names write.table(data.frame_AntiC1q_95, file="20210506_AntiC1q_95CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) #write.table(data.frame_AntiC1q_99, file="20210502_AntiC1q99CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) ``` ```{r logistic regression A15} #A15 former called A08 mycol <- c("mycol", "myCIlow", "myOdd", "myCIup") data.frame_A08_95 <- data.frame(colum_name = mycol) data.frame_A08_99 <- data.frame(colum_name = mycol) #activity logistic_active_A08<-glm(activity ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_active_A08 # x =temporary variable data.frame_A08_95 <- cbind(data.frame_A08_95, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Fever logistic_Fever_A08<- glm(FEV ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_Fever_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Fever', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Fever', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Arthritis logistic_ARI_A08 <-glm(ARI ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_ARI_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #skin involvement logistic_skin_A08<-glm(skin_involvement ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_skin_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('skin involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('skin involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Vasculitis logistic_EVA_A08 <-glm(EVA ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_EVA_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Vasculitis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Vasculitis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Pleuritis or Pericarditis logistic_PLEPER_A08 <-glm(PLEPER ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_PLEPER_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Cerebrovascular accident #table(SLEsubset$STR) #Patients with Stroke: 4/378 #leaving Stroke out in analysis due to too small sample size #logistic_STR_A08 <-glm(STR ~ A08pos., data = SLEsubset, family = "binomial") #x <- logistic_STR_A08 #data.frame_A08_95 <- cbind(data.frame_A08_95, c('Cerebrovascular accident', #exp(confint(x)[2,1]), #exp(x$coefficients[2]), #exp(confint(x)[2,2]))) #data.frame_A08_99 <- cbind(data.frame_A08_99, c('Cerebrovascular accident', #exp(confint(x, level = 0.99)[2,1]), #exp(x$coefficients[2]), #exp(confint(x, level = 0.99)[2,2]))) #CNS involvement logistic_CNS_A08 <-glm(CNSinvolvement ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_CNS_A08 round(exp(x$coefficients),3) round(exp(confint(x)),3) round(exp(confint(x, level=0.99)),4) data.frame_A08_95 <- cbind(data.frame_A08_95, c('CNS involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('CNS involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Leucopenia logistic_LEU_A08<-glm(LEU ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_LEU_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Leucopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Leucopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Thrombocytopenie logistic_PLA_A08<-glm(PLA ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_PLA_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Thrombocytopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Thrombocytopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Proteinuria logistic_Prot_A08<-glm(PRO ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_Prot_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Proteinuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Proteinuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Haematuria logistic_HUM_A08 <-glm(HUM ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_HUM_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Haematuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Haematuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #low Complement logistic_TCO_A08 <-glm(TCO ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_TCO_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('low Complement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('low Complement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #anti-ds-DNA logistic_DNA_A08 <-glm(DNA ~ A08pos., data = SLEsubset, family = "binomial") x <- logistic_DNA_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('anti-ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('anti-ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Anemia logi_Anemia_A08 <-glm(Anemia ~ A08pos., data = SLEsubset, family = "binomial") x <- logi_Anemia_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Anemia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Anemia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Ery sedimention rate logi_ESRelevated_A08 <-glm(ESRelevated ~ A08pos., data = SLEsubset, family = "binomial") x <- logi_ESRelevated_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('ESR elevated', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('ESR elevated', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Antiphospholipid Antibodies logi_APA_A08 <- glm(APA ~ A08pos., data = SLEsubset, family = "binomial") x <- logi_APA_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Antiphospholipid Antibodies', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Antiphospholipid Antibodies', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$1 Malar rash logi_ACR_Malar_rash_A08 <- glm(A1 ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Malar_rash_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Malar rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Malar rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$2 Discoid rash logi_ACR_Discoid_rash_A08 <- glm(A2 ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Discoid_rash_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Discoid rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Discoid rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$3 Photosensitivity logi_ACR_Photosensitivity_A08 <- glm(A3 ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Photosensitivity_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Photosensitivity', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Photosensitivity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$4 Nasopharyngeal ulcers logi_ACR_Nasopharyngeal_ulcers_A08 <- glm(A4 ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Nasopharyngeal_ulcers_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Nasopharyngeal ulcers', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Nasopharyngeal ulcers', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$5 Arthritis logi_ACR_Arthritis_A08 <- glm(A5 ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Arthritis_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$6 Pleuritis or Pericarditis logi_ACR_PLEPER_A08 <- glm(ACR_PLEPER ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_PLEPER_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$7 renal Disorder logi_ACR_renal_Disorder_A08 <- glm(A7 ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_renal_Disorder_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('renal Disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('renal Disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$8 neurologic disorder logi_ACR_neuro_A08 <- glm(ACR_neurologic_disorder ~ A08pos., data=SLEsubset, family = "binomial") x <-logi_ACR_neuro_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('neurologic disorder ', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('neurologic disorder ', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$9 Haematologic disorder logi_ACR_Haematologic_Disorder_A08 <- glm(A9 ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Haematologic_Disorder_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Haematologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Haematologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$10 Immunologic disorder logi_ACR_immunologic_A08 <- glm(ACR_immunologic_disorder ~ A08pos., data = SLEsubset, family = "binomial") x <- logi_ACR_immunologic_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Immunologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Immunologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti ds-DNA logi_ACR_DNA_A08 <- glm(A10a ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_DNA_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti-Sm logi_ACR_sm_A08 <- glm(A10b ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_sm_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('anti-Sm', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('anti-Sm', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_Anti-Phospholipid logi_ACR_APL_A08 <- glm(A10c ~ A08pos., data=SLEsubset, family = "binomial") x <- logi_ACR_APL_A08 data.frame_A08_95 <- cbind(data.frame_A08_95, c('Anti-Phospholipid', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08_99 <- cbind(data.frame_A08_99, c('Anti-Phospholipid', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) ``` ```{r} data.frame_A08_95 <- data.frame_A08_95 [ , c(1,seq.int(30,2))] data.frame_A08_99 <- data.frame_A08_99 [ , c(1,seq.int(30,2))] ``` ```{r} names(data.frame_A08_95) <- as.matrix(data.frame_A08_95[1,]) data.frame_A08_95 <- data.frame_A08_95[-1, ] data.frame_A08_95[] <- lapply(data.frame_A08_95, function(x) type.convert(as.character(x))) data.frame_A08_95 data.frame_A08_95$mycol <-NULL data.frame_A08_95 <- round(data.frame_A08_95,3) names(data.frame_A08_99) <- as.matrix(data.frame_A08_99[1,]) data.frame_A08_99 <- data.frame_A08_99[-1, ] data.frame_A08_99[] <- lapply(data.frame_A08_99, function(x) type.convert(as.character(x))) data.frame_A08_99 data.frame_A08_99$mycol <-NULL data.frame_A08_99 <-round(data.frame_A08_99,3) ``` ```{r} # Write a new File with tabstops as sep and no Col and Row names write.table(data.frame_A08_95, file="20210506_A08_95CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) #write.table(data.frame_A08_99, file="20210502_A0899CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) ``` ```{r logistic regression A09} #A09 former called A08shift mycol <- c("mycol", "myCIlow", "myOdd", "myCIup") data.frame_A08shift_95 <- data.frame(colum_name = mycol) data.frame_A08shift_99 <- data.frame(colum_name = mycol) #activity logistic_active_A08shift<-glm(activity ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_active_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Fever logistic_Fever_A08shift<- glm(FEV ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_Fever_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Fever', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Fever', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Arthritis logistic_ARI_A08shift <-glm(ARI ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_ARI_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #skin involvement logistic_skin_A08shift<-glm(skin_involvement ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_skin_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('skin involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('skin involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Vasculitis logistic_EVA_A08shift <-glm(EVA ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_EVA_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Vasculitis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Vasculitis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Pleuritis or Pericarditis logistic_PLEPER_A08shift <-glm(PLEPER ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_PLEPER_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Cerebrovascular accident #table(SLEsubset$STR) #Patients with Stroke: 4/378 #leaving Stroke out in analysis due to too small sample size #logistic_STR_A08shift <-glm(STR ~ A08shiftpos., data = SLEsubset, family = "binomial") #x <- logistic_STR_A08shift #data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Cerebrovascular accident', #exp(confint(x)[2,1]), #exp(x$coefficients[2]), #exp(confint(x)[2,2]))) #data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Cerebrovascular accident', #exp(confint(x, level = 0.99)[2,1]), #exp(x$coefficients[2]), #exp(confint(x, level = 0.99)[2,2]))) #CNS involvement logistic_CNS_A08shift <-glm(CNSinvolvement ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_CNS_A08shift round(exp(x$coefficients),3) round(exp(confint(x)),3) round(exp(confint(x, level=0.99)),4) data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('CNS involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('CNS involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Leucopenia logistic_LEU_A08shift<-glm(LEU ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_LEU_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Leucopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Leucopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Thrombocytopenie logistic_PLA_A08shift<-glm(PLA ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_PLA_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Thrombocytopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Thrombocytopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Proteinuria logistic_Prot_A08shift<-glm(PRO ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_Prot_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Proteinuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Proteinuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Haematuria logistic_HUM_A08shift <-glm(HUM ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_HUM_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Haematuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Haematuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #low Complement logistic_TCO_A08shift <-glm(TCO ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_TCO_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('low Complement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('low Complement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #anti-ds-DNA logistic_DNA_A08shift <-glm(DNA ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logistic_DNA_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('anti-ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('anti-ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Anemia logi_Anemia_A08shift <-glm(Anemia ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logi_Anemia_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Anemia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Anemia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Ery sedimention rate logi_ESRelevated_A08shift <-glm(ESRelevated ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logi_ESRelevated_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('ESR elevated', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('ESR elevated', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Antiphospholipid Antibodies logi_APA_A08shift <- glm(APA ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logi_APA_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Antiphospholipid Antibodies', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Antiphospholipid Antibodies', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$1 Malar rash logi_ACR_Malar_rash_A08shift <- glm(A1 ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Malar_rash_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Malar rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Malar rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$2 Discoid rash logi_ACR_Discoid_rash_A08shift <- glm(A2 ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Discoid_rash_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Discoid rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Discoid rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$3 Photosensitivity logi_ACR_Photosensitivity_A08shift <- glm(A3 ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Photosensitivity_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Photosensitivity', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Photosensitivity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$4 Nasopharyngeal ulcers logi_ACR_Nasopharyngeal_ulcers_A08shift <- glm(A4 ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Nasopharyngeal_ulcers_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Nasopharyngeal ulcers', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Nasopharyngeal ulcers', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$5 Arthritis logi_ACR_Arthritis_A08shift <- glm(A5 ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Arthritis_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$6 Pleuritis or Pericarditis logi_ACR_PLEPER_A08shift <- glm(ACR_PLEPER ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_PLEPER_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$7 renal Disorder logi_ACR_renal_Disorder_A08shift <- glm(A7 ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_renal_Disorder_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('renal Disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('renal Disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$8 neurologic disorder logi_ACR_neuro_A08shift <- glm(ACR_neurologic_disorder ~ A08shiftpos., data=SLEsubset, family = "binomial") x <-logi_ACR_neuro_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('neurologic disorder ', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('neurologic disorder ', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$9 Haematologic disorder logi_ACR_Haematologic_Disorder_A08shift <- glm(A9 ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_Haematologic_Disorder_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Haematologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Haematologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #SACR$10 Immunologic disorder logi_ACR_immunologic_A08shift <- glm(ACR_immunologic_disorder ~ A08shiftpos., data = SLEsubset, family = "binomial") x <- logi_ACR_immunologic_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Immunologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Immunologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti ds-DNA logi_ACR_DNA_A08shift <- glm(A10a ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_DNA_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti-Sm logi_ACR_sm_A08shift <- glm(A10b ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_sm_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('anti-Sm', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('anti-Sm', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_Anti-Phospholipid logi_ACR_APL_A08shift <- glm(A10c ~ A08shiftpos., data=SLEsubset, family = "binomial") x <- logi_ACR_APL_A08shift data.frame_A08shift_95 <- cbind(data.frame_A08shift_95, c('Anti-Phospholipid', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A08shift_99 <- cbind(data.frame_A08shift_99, c('Anti-Phospholipid', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) ``` ```{r} data.frame_A08shift_95 <- data.frame_A08shift_95 [ , c(1,seq.int(30,2))] data.frame_A08shift_99 <- data.frame_A08shift_99 [ , c(1,seq.int(30,2))] ``` ```{r} names(data.frame_A08shift_95) <- as.matrix(data.frame_A08shift_95[1,]) data.frame_A08shift_95 <- data.frame_A08shift_95[-1, ] data.frame_A08shift_95[] <- lapply(data.frame_A08shift_95, function(x) type.convert(as.character(x))) data.frame_A08shift_95 data.frame_A08shift_95$mycol <-NULL data.frame_A08shift_95 <- round(data.frame_A08shift_95,3) names(data.frame_A08shift_99) <- as.matrix(data.frame_A08shift_99[1,]) data.frame_A08shift_99 <- data.frame_A08shift_99[-1, ] data.frame_A08shift_99[] <- lapply(data.frame_A08shift_99, function(x) type.convert(as.character(x))) data.frame_A08shift_99 data.frame_A08shift_99$mycol <-NULL data.frame_A08shift_99 <-round(data.frame_A08shift_99,3) ``` ```{r} # Write a new File with tabstops as sep and no Col and Row names write.table(data.frame_A08shift_95, file="20210506_A08shift_95CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) #write.table(data.frame_A08shift_99, file="20210502_A08shift99CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) ``` ```{r logistic regression A86} #A86 former called A90 mycol <- c("mycol", "myCIlow", "myOdd", "myCIup") data.frame_A90_95 <- data.frame(colum_name = mycol) data.frame_A90_99 <- data.frame(colum_name = mycol) #activity logistic_active_A90<-glm(activity ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_active_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Fever logistic_Fever_A90<- glm(FEV ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_Fever_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Fever', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Fever', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Arthritis logistic_ARI_A90 <-glm(ARI ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_ARI_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #skin involvement logistic_skin_A90<-glm(skin_involvement ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_skin_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('skin involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('skin involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Vasculitis logistic_EVA_A90 <-glm(EVA ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_EVA_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Vasculitis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Vasculitis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Pleuritis or Pericarditis logistic_PLEPER_A90 <-glm(PLEPER ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_PLEPER_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Cerebrovascular accident #table(SLEsubset$STR) #Patients with Stroke: 4/378 #leaving Stroke out in analysis due to too small sample size #logistic_STR_A90 <-glm(STR ~ A90pos., data = SLEsubset, family = "binomial") #x <- logistic_STR_A90 #data.frame_A90_95 <- cbind(data.frame_A90_95, c('Cerebrovascular accident', #exp(confint(x)[2,1]), #exp(x$coefficients[2]), #exp(confint(x)[2,2]))) #data.frame_A90_99 <- cbind(data.frame_A90_99, c('Cerebrovascular accident', #exp(confint(x, level = 0.99)[2,1]), #exp(x$coefficients[2]), #exp(confint(x, level = 0.99)[2,2]))) #CNS involvement logistic_CNS_A90 <-glm(CNSinvolvement ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_CNS_A90 round(exp(x$coefficients),3) round(exp(confint(x)),3) round(exp(confint(x, level=0.99)),4) data.frame_A90_95 <- cbind(data.frame_A90_95, c('CNS involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('CNS involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Leucopenia logistic_LEU_A90<-glm(LEU ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_LEU_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Leucopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Leucopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Thrombocytopenie logistic_PLA_A90<-glm(PLA ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_PLA_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Thrombocytopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Thrombocytopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Proteinuria logistic_Prot_A90<-glm(PRO ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_Prot_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Proteinuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Proteinuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Haematuria logistic_HUM_A90 <-glm(HUM ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_HUM_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Haematuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Haematuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #low Complement logistic_TCO_A90 <-glm(TCO ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_TCO_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('low Complement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('low Complement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #anti-ds-DNA logistic_DNA_A90 <-glm(DNA ~ A90pos., data = SLEsubset, family = "binomial") x <- logistic_DNA_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('anti-ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('anti-ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Anemia logi_Anemia_A90 <-glm(Anemia ~ A90pos., data = SLEsubset, family = "binomial") x <- logi_Anemia_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Anemia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Anemia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Ery sedimention rate logi_ESRelevated_A90 <-glm(ESRelevated ~ A90pos., data = SLEsubset, family = "binomial") x <- logi_ESRelevated_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('ESR elevated', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('ESR elevated', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Antiphospholipid Antibodies logi_APA_A90 <- glm(APA ~ A90pos., data = SLEsubset, family = "binomial") x <- logi_APA_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Antiphospholipid Antibodies', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Antiphospholipid Antibodies', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$1 Malar rash logi_ACR_Malar_rash_A90 <- glm(A1 ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Malar_rash_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Malar rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Malar rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$2 Discoid rash logi_ACR_Discoid_rash_A90 <- glm(A2 ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Discoid_rash_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Discoid rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Discoid rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$3 Photosensitivity logi_ACR_Photosensitivity_A90 <- glm(A3 ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Photosensitivity_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Photosensitivity', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Photosensitivity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$4 Nasopharyngeal ulcers logi_ACR_Nasopharyngeal_ulcers_A90 <- glm(A4 ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Nasopharyngeal_ulcers_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Nasopharyngeal ulcers', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Nasopharyngeal ulcers', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$5 Arthritis logi_ACR_Arthritis_A90 <- glm(A5 ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Arthritis_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$6 Pleuritis or Pericarditis logi_ACR_PLEPER_A90 <- glm(ACR_PLEPER ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_PLEPER_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$7 renal Disorder logi_ACR_renal_Disorder_A90 <- glm(A7 ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_renal_Disorder_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('renal Disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('renal Disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$8 neurologic disorder logi_ACR_neuro_A90 <- glm(ACR_neurologic_disorder ~ A90pos., data=SLEsubset, family = "binomial") x <-logi_ACR_neuro_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('neurologic disorder ', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('neurologic disorder ', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$9 Haematologic disorder logi_ACR_Haematologic_Disorder_A90 <- glm(A9 ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Haematologic_Disorder_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Haematologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Haematologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$10 Immunologic disorder logi_ACR_immunologic_A90 <- glm(ACR_immunologic_disorder ~ A90pos., data = SLEsubset, family = "binomial") x <- logi_ACR_immunologic_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Immunologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Immunologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti ds-DNA logi_ACR_DNA_A90 <- glm(A10a ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_DNA_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti-Sm logi_ACR_sm_A90 <- glm(A10b ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_sm_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('anti-Sm', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('anti-Sm', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_Anti-Phospholipid logi_ACR_APL_A90 <- glm(A10c ~ A90pos., data=SLEsubset, family = "binomial") x <- logi_ACR_APL_A90 data.frame_A90_95 <- cbind(data.frame_A90_95, c('Anti-Phospholipid', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_A90_99 <- cbind(data.frame_A90_99, c('Anti-Phospholipid', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) ``` ```{r} data.frame_A90_95 <- data.frame_A90_95 [ , c(1,seq.int(30,2))] data.frame_A90_99 <- data.frame_A90_99 [ , c(1,seq.int(30,2))] ``` ```{r} names(data.frame_A90_95) <- as.matrix(data.frame_A90_95[1,]) data.frame_A90_95 <- data.frame_A90_95[-1, ] data.frame_A90_95[] <- lapply(data.frame_A90_95, function(x) type.convert(as.character(x))) data.frame_A90_95 data.frame_A90_95$mycol <-NULL data.frame_A90_95 <- round(data.frame_A90_95,3) names(data.frame_A90_99) <- as.matrix(data.frame_A90_99[1,]) data.frame_A90_99 <- data.frame_A90_99[-1, ] data.frame_A90_99[] <- lapply(data.frame_A90_99, function(x) type.convert(as.character(x))) data.frame_A90_99 data.frame_A90_99$mycol <-NULL data.frame_A90_99 <-round(data.frame_A90_99,3) ``` ```{r} # Write a new File with tabstops as sep and no Col and Row names write.table(data.frame_A90_95, file="20210506_A90_95CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) #write.table(data.frame_A90_99, file="20210502_A9099CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) ``` ```{r logistic regression B41} mycol <- c("mycol", "myCIlow", "myOdd", "myCIup") data.frame_B41_95 <- data.frame(colum_name = mycol) data.frame_B41_99 <- data.frame(colum_name = mycol) #activity logistic_active_B41<-glm(activity ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_active_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Fever logistic_Fever_B41<- glm(FEV ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_Fever_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Fever', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Fever', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Arthritis logistic_ARI_B41 <-glm(ARI ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_ARI_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #skin involvement logistic_skin_B41<-glm(skin_involvement ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_skin_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('skin involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('skin involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Vasculitis logistic_EVA_B41 <-glm(EVA ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_EVA_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Vasculitis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Vasculitis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Pleuritis or Pericarditis logistic_PLEPER_B41 <-glm(PLEPER ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_PLEPER_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Cerebrovascular accident table(SLEsubset$STR) #Patients with Stroke: 4/378 #leaving Stroke out in analysis due to too small sample size #logistic_STR_B41 <-glm(STR ~ B41pos., data = SLEsubset, family = "binomial") #x <- logistic_STR_B41 #data.frame_B41_95 <- cbind(data.frame_B41_95, c('Cerebrovascular accident', #exp(confint(x)[2,1]), #exp(x$coefficients[2]), #exp(confint(x)[2,2]))) #data.frame_B41_99 <- cbind(data.frame_B41_99, c('Cerebrovascular accident', #exp(confint(x, level = 0.99)[2,1]), #exp(x$coefficients[2]), #exp(confint(x, level = 0.99)[2,2]))) #CNS involvement logistic_CNS_B41 <-glm(CNSinvolvement ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_CNS_B41 round(exp(x$coefficients),3) round(exp(confint(x)),3) round(exp(confint(x, level=0.99)),4) data.frame_B41_95 <- cbind(data.frame_B41_95, c('CNS involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('CNS involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Leucopenia logistic_LEU_B41<-glm(LEU ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_LEU_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Leucopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Leucopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Thrombocytopenie logistic_PLA_B41<-glm(PLA ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_PLA_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Thrombocytopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Thrombocytopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Proteinuria logistic_Prot_B41<-glm(PRO ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_Prot_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Proteinuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Proteinuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Haematuria logistic_HUM_B41 <-glm(HUM ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_HUM_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Haematuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Haematuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #low Complement logistic_TCO_B41 <-glm(TCO ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_TCO_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('low Complement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('low Complement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #anti-ds-DNA logistic_DNA_B41 <-glm(DNA ~ B41pos., data = SLEsubset, family = "binomial") x <- logistic_DNA_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('anti-ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('anti-ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Anemia logi_Anemia_B41 <-glm(Anemia ~ B41pos., data = SLEsubset, family = "binomial") x <- logi_Anemia_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Anemia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Anemia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Ery sedimention rate logi_ESRelevated_B41 <-glm(ESRelevated ~ B41pos., data = SLEsubset, family = "binomial") x <- logi_ESRelevated_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('ESR elevated', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('ESR elevated', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Antiphospholipid Antibodies logi_APA_B41 <- glm(APA ~ B41pos., data = SLEsubset, family = "binomial") x <- logi_APA_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Antiphospholipid Antibodies', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Antiphospholipid Antibodies', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$1 Malar rash logi_ACR_Malar_rash_B41 <- glm(A1 ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Malar_rash_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Malar rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Malar rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$2 Discoid rash logi_ACR_Discoid_rash_B41 <- glm(A2 ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Discoid_rash_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Discoid rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Discoid rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$3 Photosensitivity logi_ACR_Photosensitivity_B41 <- glm(A3 ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Photosensitivity_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Photosensitivity', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Photosensitivity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$4 Nasopharyngeal ulcers logi_ACR_Nasopharyngeal_ulcers_B41 <- glm(A4 ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Nasopharyngeal_ulcers_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Nasopharyngeal ulcers', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Nasopharyngeal ulcers', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$5 Arthritis logi_ACR_Arthritis_B41 <- glm(A5 ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Arthritis_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$6 Pleuritis or Pericarditis logi_ACR_PLEPER_B41 <- glm(ACR_PLEPER ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_PLEPER_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$7 renal Disorder logi_ACR_renal_Disorder_B41 <- glm(A7 ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_renal_Disorder_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('renal Disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('renal Disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$8 neurologic disorder logi_ACR_neuro_B41 <- glm(ACR_neurologic_disorder ~ B41pos., data=SLEsubset, family = "binomial") x <-logi_ACR_neuro_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('neurologic disorder ', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('neurologic disorder ', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$9 Haematologic disorder logi_ACR_Haematologic_Disorder_B41 <- glm(A9 ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Haematologic_Disorder_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Haematologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Haematologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$10 Immunologic disorder logi_ACR_immunologic_B41 <- glm(ACR_immunologic_disorder ~ B41pos., data = SLEsubset, family = "binomial") x <- logi_ACR_immunologic_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Immunologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Immunologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti ds-DNA logi_ACR_DNA_B41 <- glm(A10a ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_DNA_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti-Sm logi_ACR_sm_B41 <- glm(A10b ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_sm_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('anti-Sm', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('anti-Sm', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_Anti-Phospholipid logi_ACR_APL_B41 <- glm(A10c ~ B41pos., data=SLEsubset, family = "binomial") x <- logi_ACR_APL_B41 data.frame_B41_95 <- cbind(data.frame_B41_95, c('Anti-Phospholipid', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B41_99 <- cbind(data.frame_B41_99, c('Anti-Phospholipid', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) ``` ```{r} data.frame_B41_95 <- data.frame_B41_95 [ , c(1,seq.int(30,2))] data.frame_B41_99 <- data.frame_B41_99 [ , c(1,seq.int(30,2))] ``` ```{r} names(data.frame_B41_95) <- as.matrix(data.frame_B41_95[1,]) data.frame_B41_95 <- data.frame_B41_95[-1, ] data.frame_B41_95[] <- lapply(data.frame_B41_95, function(x) type.convert(as.character(x))) data.frame_B41_95 data.frame_B41_95$mycol <-NULL data.frame_B41_95 <- round(data.frame_B41_95,3) names(data.frame_B41_99) <- as.matrix(data.frame_B41_99[1,]) data.frame_B41_99 <- data.frame_B41_99[-1, ] data.frame_B41_99[] <- lapply(data.frame_B41_99, function(x) type.convert(as.character(x))) data.frame_B41_99 data.frame_B41_99$mycol <-NULL data.frame_B41_99 <-round(data.frame_B41_99,3) ``` ```{r} # Write a new File with tabstops as sep and no Col and Row names write.table(data.frame_B41_95, file="20210506_B41_95CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) #write.table(data.frame_B41_99, file="20210502_B4199CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) ``` ```{r logistic regression B43} mycol <- c("mycol", "myCIlow", "myOdd", "myCIup") data.frame_B43_95 <- data.frame(colum_name = mycol) data.frame_B43_99 <- data.frame(colum_name = mycol) #activity logistic_active_B43<-glm(activity ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_active_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Fever logistic_Fever_B43<- glm(FEV ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_Fever_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Fever', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Fever', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Arthritis logistic_ARI_B43 <-glm(ARI ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_ARI_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #skin involvement logistic_skin_B43<-glm(skin_involvement ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_skin_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('skin involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('skin involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Vasculitis logistic_EVA_B43 <-glm(EVA ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_EVA_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Vasculitis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Vasculitis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Pleuritis or Pericarditis logistic_PLEPER_B43 <-glm(PLEPER ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_PLEPER_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Cerebrovascular accident table(SLEsubset$STR) #Patients with Stroke: 4/378 #leaving Stroke out in analysis due to too small sample size #logistic_STR_B43 <-glm(STR ~ B43pos., data = SLEsubset, family = "binomial") #x <- logistic_STR_B43 #data.frame_B43_95 <- cbind(data.frame_B43_95, c('Cerebrovascular accident', #exp(confint(x)[2,1]), #exp(x$coefficients[2]), #exp(confint(x)[2,2]))) #data.frame_B43_99 <- cbind(data.frame_B43_99, c('Cerebrovascular accident', #exp(confint(x, level = 0.99)[2,1]), #exp(x$coefficients[2]), #exp(confint(x, level = 0.99)[2,2]))) #CNS involvement logistic_CNS_B43 <-glm(CNSinvolvement ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_CNS_B43 round(exp(x$coefficients),3) round(exp(confint(x)),3) round(exp(confint(x, level=0.99)),4) data.frame_B43_95 <- cbind(data.frame_B43_95, c('CNS involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('CNS involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Leucopenia logistic_LEU_B43<-glm(LEU ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_LEU_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Leucopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Leucopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Thrombocytopenie logistic_PLA_B43<-glm(PLA ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_PLA_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Thrombocytopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Thrombocytopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Proteinuria logistic_Prot_B43<-glm(PRO ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_Prot_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Proteinuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Proteinuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Haematuria logistic_HUM_B43 <-glm(HUM ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_HUM_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Haematuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Haematuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #low Complement logistic_TCO_B43 <-glm(TCO ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_TCO_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('low Complement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('low Complement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #anti-ds-DNA logistic_DNA_B43 <-glm(DNA ~ B43pos., data = SLEsubset, family = "binomial") x <- logistic_DNA_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('anti-ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('anti-ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Anemia logi_Anemia_B43 <-glm(Anemia ~ B43pos., data = SLEsubset, family = "binomial") x <- logi_Anemia_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Anemia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Anemia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Ery sedimention rate logi_ESRelevated_B43 <-glm(ESRelevated ~ B43pos., data = SLEsubset, family = "binomial") x <- logi_ESRelevated_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('ESR elevated', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('ESR elevated', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Antiphospholipid Antibodies logi_APA_B43 <- glm(APA ~ B43pos., data = SLEsubset, family = "binomial") x <- logi_APA_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Antiphospholipid Antibodies', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Antiphospholipid Antibodies', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$1 Malar rash logi_ACR_Malar_rash_B43 <- glm(A1 ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Malar_rash_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Malar rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Malar rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$2 Discoid rash logi_ACR_Discoid_rash_B43 <- glm(A2 ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Discoid_rash_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Discoid rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Discoid rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$3 Photosensitivity logi_ACR_Photosensitivity_B43 <- glm(A3 ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Photosensitivity_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Photosensitivity', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Photosensitivity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$4 Nasopharyngeal ulcers logi_ACR_Nasopharyngeal_ulcers_B43 <- glm(A4 ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Nasopharyngeal_ulcers_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Nasopharyngeal ulcers', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Nasopharyngeal ulcers', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$5 Arthritis logi_ACR_Arthritis_B43 <- glm(A5 ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Arthritis_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$6 Pleuritis or Pericarditis logi_ACR_PLEPER_B43 <- glm(ACR_PLEPER ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_PLEPER_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$7 renal Disorder logi_ACR_renal_Disorder_B43 <- glm(A7 ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_renal_Disorder_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('renal Disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('renal Disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$8 neurologic disorder logi_ACR_neuro_B43 <- glm(ACR_neurologic_disorder ~ B43pos., data=SLEsubset, family = "binomial") x <-logi_ACR_neuro_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('neurologic disorder ', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('neurologic disorder ', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$9 Haematologic disorder logi_ACR_Haematologic_Disorder_B43 <- glm(A9 ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Haematologic_Disorder_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Haematologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Haematologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$10 Immunologic disorder logi_ACR_immunologic_B43 <- glm(ACR_immunologic_disorder ~ B43pos., data = SLEsubset, family = "binomial") x <- logi_ACR_immunologic_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Immunologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Immunologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti ds-DNA logi_ACR_DNA_B43 <- glm(A10a ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_DNA_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti-Sm logi_ACR_sm_B43 <- glm(A10b ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_sm_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('anti-Sm', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('anti-Sm', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_Anti-Phospholipid logi_ACR_APL_B43 <- glm(A10c ~ B43pos., data=SLEsubset, family = "binomial") x <- logi_ACR_APL_B43 data.frame_B43_95 <- cbind(data.frame_B43_95, c('Anti-Phospholipid', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B43_99 <- cbind(data.frame_B43_99, c('Anti-Phospholipid', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) ``` ```{r} data.frame_B43_95 <- data.frame_B43_95 [ , c(1,seq.int(30,2))] data.frame_B43_99 <- data.frame_B43_99 [ , c(1,seq.int(30,2))] ``` ```{r} names(data.frame_B43_95) <- as.matrix(data.frame_B43_95[1,]) data.frame_B43_95 <- data.frame_B43_95[-1, ] data.frame_B43_95[] <- lapply(data.frame_B43_95, function(x) type.convert(as.character(x))) data.frame_B43_95 data.frame_B43_95$mycol <-NULL data.frame_B43_95 <- round(data.frame_B43_95,3) names(data.frame_B43_99) <- as.matrix(data.frame_B43_99[1,]) data.frame_B43_99 <- data.frame_B43_99[-1, ] data.frame_B43_99[] <- lapply(data.frame_B43_99, function(x) type.convert(as.character(x))) data.frame_B43_99 data.frame_B43_99$mycol <-NULL data.frame_B43_99 <-round(data.frame_B43_99,3) ``` ```{r} # Write a new File with tabstops as sep and no Col and Row names write.table(data.frame_B43_95, file="20210506_B43_95CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) #write.table(data.frame_B43_99, file="20210502_B4399CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) ``` ```{r logistic regression B83} mycol <- c("mycol", "myCIlow", "myOdd", "myCIup") data.frame_B83_95 <- data.frame(colum_name = mycol) data.frame_B83_99 <- data.frame(colum_name = mycol) #activity logistic_active_B83<-glm(activity ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_active_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Activity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Fever logistic_Fever_B83<- glm(FEV ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_Fever_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Fever', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Fever', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Arthritis logistic_ARI_B83 <-glm(ARI ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_ARI_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #skin involvement logistic_skin_B83<-glm(skin_involvement ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_skin_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('skin involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('skin involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Vasculitis logistic_EVA_B83 <-glm(EVA ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_EVA_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Vasculitis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Vasculitis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Pleuritis or Pericarditis logistic_PLEPER_B83 <-glm(PLEPER ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_PLEPER_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Cerebrovascular accident table(SLEsubset$STR) #Patients with Stroke: 4/378 #leaving Stroke out in analysis due to too small sample size #logistic_STR_B83 <-glm(STR ~ B83pos., data = SLEsubset, family = "binomial") #x <- logistic_STR_B83 #data.frame_B83_95 <- cbind(data.frame_B83_95, c('Cerebrovascular accident', #exp(confint(x)[2,1]), #exp(x$coefficients[2]), #exp(confint(x)[2,2]))) #data.frame_B83_99 <- cbind(data.frame_B83_99, c('Cerebrovascular accident', #exp(confint(x, level = 0.99)[2,1]), #exp(x$coefficients[2]), #exp(confint(x, level = 0.99)[2,2]))) #CNS involvement logistic_CNS_B83 <-glm(CNSinvolvement ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_CNS_B83 round(exp(x$coefficients),3) round(exp(confint(x)),3) round(exp(confint(x, level=0.99)),4) data.frame_B83_95 <- cbind(data.frame_B83_95, c('CNS involvement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('CNS involvement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Leucopenia logistic_LEU_B83<-glm(LEU ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_LEU_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Leucopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Leucopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Thrombocytopenie logistic_PLA_B83<-glm(PLA ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_PLA_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Thrombocytopenia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Thrombocytopenia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Proteinuria logistic_Prot_B83<-glm(PRO ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_Prot_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Proteinuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Proteinuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Haematuria logistic_HUM_B83 <-glm(HUM ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_HUM_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Haematuria', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Haematuria', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #low Complement logistic_TCO_B83 <-glm(TCO ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_TCO_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('low Complement', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('low Complement', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #anti-ds-DNA logistic_DNA_B83 <-glm(DNA ~ B83pos., data = SLEsubset, family = "binomial") x <- logistic_DNA_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('anti-ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('anti-ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Anemia logi_Anemia_B83 <-glm(Anemia ~ B83pos., data = SLEsubset, family = "binomial") x <- logi_Anemia_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Anemia', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Anemia', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Ery sedimention rate logi_ESRelevated_B83 <-glm(ESRelevated ~ B83pos., data = SLEsubset, family = "binomial") x <- logi_ESRelevated_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('ESR elevated', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('ESR elevated', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #Antiphospholipid Antibodies logi_APA_B83 <- glm(APA ~ B83pos., data = SLEsubset, family = "binomial") x <- logi_APA_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Antiphospholipid Antibodies', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Antiphospholipid Antibodies', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$1 Malar rash logi_ACR_Malar_rash_B83 <- glm(A1 ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Malar_rash_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Malar rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Malar rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$2 Discoid rash logi_ACR_Discoid_rash_B83 <- glm(A2 ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Discoid_rash_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Discoid rash', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Discoid rash', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$3 Photosensitivity logi_ACR_Photosensitivity_B83 <- glm(A3 ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Photosensitivity_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Photosensitivity', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Photosensitivity', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$4 Nasopharyngeal ulcers logi_ACR_Nasopharyngeal_ulcers_B83 <- glm(A4 ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Nasopharyngeal_ulcers_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Nasopharyngeal ulcers', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Nasopharyngeal ulcers', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$5 Arthritis logi_ACR_Arthritis_B83 <- glm(A5 ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Arthritis_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Arthritis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Arthritis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$6 Pleuritis or Pericarditis logi_ACR_PLEPER_B83 <- glm(ACR_PLEPER ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_PLEPER_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Pleuritis or Pericarditis', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Pleuritis or Pericarditis', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$7 renal Disorder logi_ACR_renal_Disorder_B83 <- glm(A7 ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_renal_Disorder_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('renal Disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('renal Disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$8 neurologic disorder logi_ACR_neuro_B83 <- glm(ACR_neurologic_disorder ~ B83pos., data=SLEsubset, family = "binomial") x <-logi_ACR_neuro_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('neurologic disorder ', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('neurologic disorder ', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$9 Haematologic disorder logi_ACR_Haematologic_Disorder_B83 <- glm(A9 ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_Haematologic_Disorder_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Haematologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Haematologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR$10 Immunologic disorder logi_ACR_immunologic_B83 <- glm(ACR_immunologic_disorder ~ B83pos., data = SLEsubset, family = "binomial") x <- logi_ACR_immunologic_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Immunologic disorder', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Immunologic disorder', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti ds-DNA logi_ACR_DNA_B83 <- glm(A10a ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_DNA_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('ds-DNA', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('ds-DNA', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_anti-Sm logi_ACR_sm_B83 <- glm(A10b ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_sm_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('anti-Sm', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('anti-Sm', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) #ACR_Anti-Phospholipid logi_ACR_APL_B83 <- glm(A10c ~ B83pos., data=SLEsubset, family = "binomial") x <- logi_ACR_APL_B83 data.frame_B83_95 <- cbind(data.frame_B83_95, c('Anti-Phospholipid', exp(confint(x)[2,1]), exp(x$coefficients[2]), exp(confint(x)[2,2]))) data.frame_B83_99 <- cbind(data.frame_B83_99, c('Anti-Phospholipid', exp(confint(x, level = 0.99)[2,1]), exp(x$coefficients[2]), exp(confint(x, level = 0.99)[2,2]))) ``` ```{r} data.frame_B83_95 <- data.frame_B83_95 [ , c(1,seq.int(30,2))] data.frame_B83_99 <- data.frame_B83_99 [ , c(1,seq.int(30,2))] ``` ```{r} names(data.frame_B83_95) <- as.matrix(data.frame_B83_95[1,]) data.frame_B83_95 <- data.frame_B83_95[-1, ] data.frame_B83_95[] <- lapply(data.frame_B83_95, function(x) type.convert(as.character(x))) data.frame_B83_95 data.frame_B83_95$mycol <-NULL data.frame_B83_95 <- round(data.frame_B83_95,3) names(data.frame_B83_99) <- as.matrix(data.frame_B83_99[1,]) data.frame_B83_99 <- data.frame_B83_99[-1, ] data.frame_B83_99[] <- lapply(data.frame_B83_99, function(x) type.convert(as.character(x))) data.frame_B83_99 data.frame_B83_99$mycol <-NULL data.frame_B83_99 <-round(data.frame_B83_99,3) ``` ```{r} # Write a new File with tabstops as sep and no Col and Row names write.table(data.frame_B83_95, file="20210506_B83_95CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) #write.table(data.frame_B83_99, file="20210502_B8399CI.txt", append = FALSE, sep = "\t", dec = ".", row.names = F) ```