#adapted from my structure.diagram function to draw the output from esem
#August 4, 2016
"esem.diagram" <-
function(esem=NULL,labels=NULL,cut=.3,errors=FALSE,simple=TRUE,regression=FALSE,lr=TRUE,
digits=1,e.size=.1,adj=2,main="Exploratory Structural Model", ...){
#a helper function
sort.f <- function(x) {
nvar <- ncol(x)
if(is.null(nvar)) {return(x)} else {
nitem <- nrow(x)
cluster <- data.frame(item <- seq(1:nitem),clust = rep(0,nitem))
cluster$clust <- apply(abs(x),1,which.max)
ord <- sort(cluster$clust,index.return=TRUE)
x[1:nitem,] <- x[ord$ix,]
rownames(x) <- rownames(x)[ord$ix]
return(x)}}
#first some default values
xmodel <- sort.f(esem$loadsX)
ymodel <- sort.f(esem$loadsY)
Phi <- esem$Phi
num.y <- num.x <- 0 #we assume there is nothing there
vars<- NULL
num.xvar <- dim(xmodel)[1] #how many x variables?
num.yvar <- dim(ymodel)[1]
num.xfactors <- dim(xmodel)[2]
num.yfactors <- dim(ymodel)[2]
if(is.null(num.xvar)) num.xvar <- length(xmodel)
if(is.null(num.yvar)) num.yvar <- length(ymodel)
if(is.null(num.xfactors)) num.xfactors <- 1
if(is.null(num.yfactors)) num.yfactors <- 1
# if(max(num.xvar,num.yvar) < 10) e.size <- e.size* 2 #make the ellipses bigger for small problems
e.size <- e.size * 10/ max(num.xvar,num.yvar)
if(is.null(labels)) { xvars <- rownames(xmodel)} else { xvars <- vars <- labels}
if(is.null(ncol(xmodel))) xvars <- names(xmodel)
# if(is.null(vars) ) {xvars <- paste0("x",1:num.xvar) }
fact <- colnames(xmodel)
if (is.null(fact)) { fact <- paste0("X",1:num.xfactors) }
if(is.null(ncol(ymodel))) {yvars <-names(ymodel) } else {yvars <- rownames(ymodel)}
if(is.null(yvars)) {yvars <- paste0("y",1:num.y) }
if(is.null(labels)) {vars <- c(xvars,yvars)} else {yvars <- labels[(num.xvar+1):(num.xvar+num.y)]}
yfact <- colnames(ymodel)
if(is.null(yfact)) {yfact <- paste0("Y",1:num.yfactors) }
fact <- c(fact,yfact)
num.var <- num.xvar + num.y
num.factors <- num.xfactors + num.yfactors
sem <- matrix(rep(NA),6*(num.var*num.factors + num.factors),ncol=3) #this creates an output model for sem analysis
colnames(sem) <- c("Path","Parameter","Value")
var.rect <- list()
fact.rect <- list()
#
length.labels <- 0 # a filler for now
#plot.new() is necessary if we have not plotted before
#strwd <- try(strwidth(xvars),silent=TRUE)
strwd <- try(length.labels <- max(strwidth(xvars),strwidth(yvars),strwidth("abc"))/1.8,silent=TRUE) #although this throws an error if the window is not already open, we don't show it
#if (class(strwd) == "try-error" ) {plot.new() }
if (class(strwd) == "try-error" ) {length.labels = max(nchar(xvars),3)/1.8 }
#length.labels <- max(strwidth(xvars),strwidth("abc"))/1.8
if(lr) {limx <- c(-(length.labels),max(num.xvar,num.yvar)+3 )
limy <- c(0,max(num.xvar,num.yvar)+1) } else {
limy <- c(-(length.labels),max(num.xvar,num.yvar) +3 )
limx <- c(0,max(num.xvar,num.yvar)+1)
if( errors) limy <- c(-1,max(num.xvar,num.yvar)+2)}
scale.xaxis <- 3
if(lr) {plot(0,type="n",xlim=limx,ylim=limy,frame.plot=FALSE,axes=FALSE,ylab="",xlab="",main=main)} else {plot(0,type="n",xlim=limx,ylim=limy,frame.plot=FALSE,axes=FALSE,ylab="",xlab="",main=main) }
#now draw the x part
k <- num.factors
x.adjust <- num.xvar/ max(num.xvar,num.yvar)
for (v in 1:num.xvar) {
if(lr) { var.rect[[v]] <- dia.rect(0,(num.xvar-v+1)/x.adjust,xvars[v],xlim=limx,ylim=limy,...) } else { var.rect[[v]] <- dia.rect(v,0,xvars[v],xlim=limy,ylim=limx,...) }
}
nvar <- num.xvar
f.scale <- (num.xvar+ 1)/(num.xfactors+1)/x.adjust
factors <- round(xmodel,digits)
if(is.null(ncol(factors))) factors <- matrix(factors)
if (num.xfactors >0) {
for (f in 1:num.xfactors) {
if(!regression) {if(lr) {fact.rect[[f]] <- dia.ellipse(limx[2]/scale.xaxis,(num.xfactors+1-f)*f.scale,fact[f],xlim=c(0,nvar),ylim=c(0,nvar),e.size=e.size,...)} else {fact.rect[[f]] <- dia.ellipse(f*f.scale,limy[2]/scale.xaxis,fact[f],ylim=c(0,nvar),xlim=c(0,nvar),e.size=e.size,...)
}
} else {if(lr) {fact.rect[[f]] <- dia.rect(limx[2]/scale.xaxis,(num.xfactors+1-f)*f.scale,fact[f],xlim=c(0,nvar),ylim=c(0,nvar),...)} else {
fact.rect[[f]] <- dia.rect(f*f.scale,limy[2]/scale.xaxis,fact[f],xlim=c(0,nvar),ylim=c(0,nvar),...)}
}
for (v in 1:num.xvar) {
if(is.numeric(factors[v,f])) {
if(simple && (abs(factors[v,f]) == max(abs(factors[v,])) ) && (abs(factors[v,f]) > cut) | (!simple && (abs(factors[v,f]) > cut))) { if (!regression) {if(lr){dia.arrow(from=fact.rect[[f]],to=var.rect[[v]]$right,labels =factors[v,f],col=((sign(factors[v,f])<0) +1),lty=((sign(factors[v,f])<0) +1),adj=f %% adj +1)
} else {dia.arrow(from=fact.rect[[f]],to=var.rect[[v]]$top,labels =factors[v,f],col=((sign(factors[v,f])<0) +1),lty=((sign(factors[v,f])<0) +1))
}
} else {dia.arrow(to=fact.rect[[f]]$left,from=var.rect[[v]]$right,labels =factors[v,f],col=((sign(factors[v,f])<0) +1))} }
} else {
if (factors[v,f] !="0") {
if (!regression) { if(lr) {dia.arrow(from=fact.rect[[f]],to=var.rect[[v]]$right,labels =factors[v,f]) } else {dia.arrow(from=fact.rect[[f]],to=var.rect[[v]]$top,labels =factors[v,f])}
} else {if(lr) {dia.arrow(to=fact.rect[[f]],from=var.rect[[v]]$right,labels =factors[v,f])} else {dia.arrow(to=fact.rect[[f]],from=var.rect[[v]]$top,labels =factors[v,f])}
} }
} }
}
if (num.xfactors ==1) {
for(i in 1:num.xvar) {
sem[i,1] <- paste(fact[1],"->",vars[i],sep="")
if(is.numeric(factors[i])) {sem[i,2] <- vars[i]} else {sem[i,2] <- factors[i] }
}} #end of if num.xfactors ==1
k <- num.xvar+1
k <- 1
for (i in 1:num.xvar) {
for (f in 1:num.xfactors) { #if (!is.numeric(factors[i,f]) || (abs(factors[i,f]) > cut))
if((!is.numeric(factors[i,f] ) && (factors[i,f] !="0"))|| ((is.numeric(factors[i,f]) && abs(factors[i,f]) > cut ))) {
sem[k,1] <- paste(fact[f],"->",vars[i],sep="")
if(is.numeric(factors[i,f])) {sem[k,2] <- paste("F",f,vars[i],sep="")} else {sem[k,2] <- factors[i,f]}
k <- k+1 } #end of if
}
}
} #end of if num.xfactors >0
if(errors) { for (i in 1:num.xvar) {if(lr) { dia.self(var.rect[[i]],side=2) } else { dia.self(var.rect[[i]],side=1)}
sem[k,1] <- paste(vars[i],"<->",vars[i],sep="")
sem[k,2] <- paste("x",i,"e",sep="")
k <- k+1 }
}
#do it for y model
if(!is.null(ymodel)) {
if(lr) { y.adj <- num.yvar/ max(num.xvar,num.yvar)
#y.adj <- num.yvar/2 - num.xvar/2
f.yscale <- limy[2]/(num.yfactors+1)
y.fadj <- 0} else {
# y.adj <- num.xvar/2 - num.yvar/2
y.adj <- num.yvar/2
f.yscale <- limx[2]/(num.yfactors+1)
y.fadj <- 0}
for (v in 1:num.yvar) { if(lr){ var.rect[[v+num.xvar]] <- dia.rect(limx[2]-.35,limy[2]-v /y.adj,yvars[v],xlim=limx,ylim=limy,...)} else {
var.rect[[v+num.xvar]] <- dia.rect(v / y.adj,limx[2],yvars[v],xlim=limy,ylim=limx,...)}
}
}
#we have drawn the y variables, now should we draw the Y factors
if(!is.null(ymodel)){
y.factors <- round(ymodel,digits)
if(is.null(ncol(y.factors))) { y.factors <- matrix(y.factors) }
num.y <- nrow(y.factors)
for (f in 1:num.yfactors) {if(lr) {
fact.rect[[f+num.xfactors]] <- dia.ellipse(2*limx[2]/scale.xaxis,(num.yfactors+1-f)*f.yscale +y.fadj,yfact[f],xlim=c(0,nvar),ylim=c(0,nvar),e.size=e.size,...)} else {
fact.rect[[f+num.xfactors]] <- dia.ellipse(f*f.yscale+ y.fadj,2*limx[2]/scale.xaxis,yfact[f],ylim=c(0,nvar),xlim=c(0,nvar),e.size=e.size,...)}
for (v in 1:num.yvar) {if(is.numeric(y.factors[v,f])) {
{if(simple && (abs(y.factors[v,f]) == max(abs(y.factors[v,])) ) && (abs(y.factors[v,f]) > cut) | (!simple && (abs(factors[v,f]) > cut))) {
if(lr) { dia.arrow(from=fact.rect[[f+num.xfactors]],to=var.rect[[v+num.xvar]]$left,labels =y.factors[v,f],col=((sign(y.factors[v,f])<0) +1),adj = f %% adj +1)} else {
dia.arrow(from=fact.rect[[f+num.xfactors]],to=var.rect[[v+num.xvar]]$bottom,labels =y.factors[v,f],col=((sign(y.factors[v,f])<0) +1))}
}
}
} else {if(factors[v,f] !="0") {if(lr) {dia.arrow(from=fact.rect[[f+num.xfactors]],to=var.rect[[v+num.xvar]]$left,labels =y.factors[v,f]) } else {
dia.arrow(from=fact.rect[[f+num.xfactors]],to=var.rect[[v+num.xvar]]$bottom,labels =y.factors[v,f])
}
}
}}
}
if (num.yfactors ==1) {
for (i in 1:num.y) { sem[k,1] <- paste(fact[1+num.xfactors],"->",yvars[i],sep="")
if(is.numeric(y.factors[i] ) ) {sem[k,2] <- paste("Fy",yvars[i],sep="")} else {sem[k,2] <- y.factors[i]}
k <- k +1
}
} else { #end of if num.yfactors ==1
for (i in 1:num.y) {
for (f in 1:num.yfactors) {
if( abs(y.factors[i,f]) > cut ) {
sem[k,1] <- paste(fact[f+num.xfactors],"->",vars[i+num.xvar],sep="")
if(is.numeric(y.factors[i,f])) { sem[k,2] <- paste("Fy",f,vars[i+num.xvar],sep="")} else {sem[k,2] <- y.factors[i,f]}
k <- k+1 } #end of if
} #end of factor
} # end of variable loop
} #end of else if
# }
if(errors) { for (i in 1:num.y) {
if(lr) {dia.self(var.rect[[i+num.xvar]],side=3) } else {dia.self(var.rect[[i+num.xvar]],side=3)}
sem[k,1] <- paste(vars[i+num.xvar],"<->",vars[i+num.xvar],sep="")
sem[k,2] <- paste("y",i,"e",sep="")
k <- k+1 }}
} #end of if.null(ymodel)
# if(!is.null(Rx)) {#draw the correlations between the x variables
# for (i in 2:num.xvar) {
# for (j in 1:(i-1)) {
# if((!is.numeric(Rx[i,j] ) && ((Rx[i,j] !="0")||(Rx[j,i] !="0")))|| ((is.numeric(Rx[i,j]) && abs(Rx[i,j]) > cut ))) {
# if (lr) {if(abs(i-j) < 2) { dia.curve(from=var.rect[[j]]$left,to=var.rect[[i]]$left, labels = Rx[i,j],scale=-3*(i-j)/num.xvar)} else { dia.curve(from=var.rect[[j]]$left,to=var.rect[[i]]$left, labels = Rx[i,j],scale=-3*(i-j)/num.xvar)}
# } else {
# if(abs(i-j) < 2) { dia.curve(from=var.rect[[j]]$bottom,to=var.rect[[i]]$bottom, labels = Rx[i,j],scale=-3*(i-j)/num.xvar)} else {dia.curve(from=var.rect[[j]]$bottom,to=var.rect[[i]]$bottom, labels = Rx[i,j],scale=-3*(i-j)/num.xvar)}
# }
# }}
# }
#
# }
# if(!is.null(Ry)) {#draw the correlations between the y variables
# for (i in 2:num.yvar) {
# for (j in 1:(i-1)) {
# if((!is.numeric(Ry[i,j] ) && ((Ry[i,j] !="0")||(Ry[j,i] !="0")))|| ((is.numeric(Ry[i,j]) && abs(Ry[i,j]) > cut ))) {
# if (lr) {if(abs(i-j) < 2) { dia.curve(from=var.rect[[j+num.xvar]]$right,to=var.rect[[i+num.xvar]]$right, labels = Ry[i,j],scale=3*(i-j)/num.xvar)} else {dia.curve(from=var.rect[[j+num.xvar]]$right,to=var.rect[[i+num.xvar]]$right, labels = Ry[i,j],scale=3*(i-j)/num.xvar)}
# } else {
# if(abs(i-j) < 2) { dia.curve(from=var.rect[[j+num.xvar]]$bottom,to=var.rect[[i+num.xvar]]$bottom, labels = Ry[i,j],scale=3*(i-j)/num.xvar)} else {dia.curve(from=var.rect[[j+num.xvar]]$bottom,to=var.rect[[i+num.xvar]]$bottom, labels = Ry[i,j],scale=3*(i-j)/num.xvar)}
# }
# }}
# }
#
# }
Phi <- round(Phi,digits)
if(!regression) {
if(!is.null(Phi)) {if (!is.matrix(Phi)) { if(!is.null(FALSE)) {Phi <- matrix(c(1,0,Phi,1),ncol=2)} else {Phi <- matrix(c(1,Phi,Phi,1),ncol=2)}}
if(num.xfactors>1) {for (i in 2:num.xfactors) { #first do the correlations within the f set
for (j in 1:(i-1)) {
{if((!is.numeric(Phi[i,j] ) && ((Phi[i,j] !="0")||(Phi[j,i] !="0")))|| ((is.numeric(Phi[i,j]) && abs(Phi[i,j]) > cut ))) {
if(Phi[i,j] == Phi[j,i] ) {
if(lr) {dia.curve(from=fact.rect[[i]]$right,to=fact.rect[[j]]$right, labels = Phi[i,j],scale=2*(i-j)/num.xfactors)} else {
dia.curve(from=fact.rect[[i]]$top,to=fact.rect[[j]]$top, labels = Phi[i,j],scale=2*(i-j)/num.xfactors)}
sem[k,1] <- paste(fact[i],"<->",fact[j],sep="")
sem[k,2] <- paste("rF",i,"F",j,sep="")} else {#directed arrows
if(Phi[i,j] !="0") { if(lr) { if(abs(i-j) < 2) {dia.arrow(from=fact.rect[[j]],to=fact.rect[[i]], labels = Phi[i,j],scale=2*(i-j)/num.xfactors)} else {
dia.curved.arrow(from=fact.rect[[j]]$right,to=fact.rect[[i]]$right, labels = Phi[i,j],scale=2*(i-j)/num.xfactors)}
} else {
if(abs(i-j) < 2) { dia.arrow(from=fact.rect[[j]],to=fact.rect[[i]], labels = Phi[i,j],scale=2*(i-j)/num.xfactors)} else {
dia.curved.arrow(from=fact.rect[[j]]$top,to=fact.rect[[i]]$top, labels = Phi[i,j],scale=2*(i-j)/num.xfactors)}
}
sem[k,1] <- paste(fact[j]," ->",fact[i],sep="")
sem[k,2] <- paste("rF",j,"F",i,sep="")} else {
if(lr) { if(abs(i-j) < 2) {dia.arrow(from=fact.rect[[i]],to=fact.rect[[j]], labels = Phi[j,i],scale=2*(i-j)/num.xfactors)} else {
dia.curved.arrow(from=fact.rect[[i]]$right,to=fact.rect[[j]]$right, labels = Phi[j,i],scale=2*(i-j)/num.xfactors)}
} else {
if(abs(i-j) < 2) { dia.arrow(from=fact.rect[[i]],to=fact.rect[[j]], labels = Phi[j,i],scale=2*(i-j)/num.xfactors)} else {
dia.curved.arrow(from=fact.rect[[i]]$top,to=fact.rect[[j]]$top, labels = Phi[j,i],scale=2*(i-j)/num.xfactors)}
}
sem[k,1] <- paste(fact[i],"<-",fact[j],sep="")
sem[k,2] <- paste("rF",i,"F",j,sep="")}
} } else {
sem[k,1] <- paste(fact[i],"<->",fact[j],sep="")
if (is.numeric(Phi[i,j])) {sem[k,2] <- paste("rF",i,"F",j,sep="")} else {sem[k,2] <- Phi[i,j] } }
k <- k + 1} }
}
} #end of correlations within the fx set
if(!is.null(ymodel)) {
for (i in 1:num.xfactors) {
for (j in 1:num.yfactors) {
if((!is.numeric(Phi[j+num.xfactors,i] ) && (Phi[j+num.xfactors,i] !="0"))|| ((is.numeric(Phi[j+num.xfactors,i]) && abs(Phi[j+num.xfactors,i]) > cut ))) {
dia.arrow(from=fact.rect[[i]],to=fact.rect[[j+num.xfactors]],Phi[j+num.xfactors,i],adj=i %% adj +1)
sem[k,1] <- paste(fact[i],"->",fact[j+num.xfactors],sep="") } else {
sem[k,1] <- paste(fact[i],"<->",fact[j+num.xfactors],sep="")}
if (is.numeric(Phi[j+num.xfactors,i])) {sem[k,2] <- paste("rX",i,"Y",j,sep="")} else {sem[k,2] <- Phi[j+num.xfactors,i] }
k <- k + 1 }
} }
} }
if(num.factors > 0 ) {
for(f in 1:num.factors) {
sem[k,1] <- paste(fact[f],"<->",fact[f],sep="")
sem[k,3] <- "1"
k <- k+1
}
model=sem[1:(k-1),]
class(model) <- "mod" #suggested by John Fox to make the output cleaner
return(invisible(model)) }
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.