library("lavaan") library("semPlot") library("dismo") library("gbm") library("vegan") library(MuMIn) tmp=mydata data1=as.data.frame(apply(tmp[,-c(1,2)],2,function(x)(x-mean(x))/sd(x))) model <- ' # latent variable topo=~Top_slope envi=~Soil_pca1 div=~PD stand=~dbh.cv trait=~CWM_sla #bacter.sp fung.shan soildiv=~fung.shan #regressions div+stand+trait+soildiv+envi~topo trait+div+soildiv+stand~envi stand~div+trait soildiv~stand meanFunction~envi+div+stand+trait+soildiv+topo' fit2<- sem(model ,data=data1) fitMeasures(fit2, c("cfi", "rmsea", "srmr","chisq","pvalue")) summary(fit2,standardized=TRUE, fit.measures=TRUE, rsquare=TRUE) standardizedSolution(fit2) AIC(fit2)