Plotting Dewey and Lu path analysis results as a Path diagram in R

Question

I am trying to plot the outputs of a path analysis suggested by Dewey and Lu (1959) in R.

require(agricolae)
require(Hmisc)

data(wilt)
data(soil)
x<-soil[,c(3,12,14,20)]
y<-wilt[,14]
data <- cbind(y,x)
#Correlation of independant variables
cor.x <- rcorr(as.matrix(x))$r
#Correlation of dependant variable with all the independant variables
cor.y <- as.data.frame(t(subset(rcorr(as.matrix(cbind(y,x)))$r, select = c(y))))[,-1]
#Path Analysis
Path <- path.analysis(cor.x,cor.y)
#Direct Effects
diag(Path$Coeff)
#Residual Effects
Path$Residual

I want to plot the direct effects of independent variables to the dependent variable y and the correlations among the dependent variables as follows along with the residual effect.

enter image description here

I have tried semPlot and path.diagram {sem} and qgraph.lavaan, but they plot the model only. pathdiagram does not plot edge labels (path coefficients and correlations). How to do it in R?

This is as far as I got using the `diagram package.

par(mar = c(1, 1, 1, 1))
openplotmat()
# Get plot coordinates
elpos <- coordinates (c(2, length(cor.y)))
# adjust coordinates for Residual
elpos[2,1] <- abs((elpos[1,1]+elpos[1,2])/2)


#Specify Arrow positions
#1 Residual to Dependent
ft1 <- matrix(ncol = 2, byrow = TRUE, data = c(1, 2))
#2 Independent to dependent
ft2 <- matrix(ncol=2, byrow = FALSE, 
              data= c(seq((2+length(cor.y)))[3:(length(cor.y)+2)], rep(2, length(cor.y))))
#3 For cor.x
fromto_CU <- t(combn(seq((2+length(cor.y)))[3:(length(cor.y)+2)],2))
#4 For path distances
fromto_ST <- rbind(ft1,ft2)

# Plot Path distance arrows
nr <- nrow(fromto_ST)
arrpos <- matrix(ncol = 2, nrow = nr)
for (i in 1:nr)
  arrpos[i, ] <- straightarrow (to = elpos[fromto_ST[i, 2], ],
                                from = elpos[fromto_ST[i, 1], ],
                                lwd = 2, arr.pos = 0.6, arr.length = 0.5)

#Label residual path distance arrow
text(arrpos[1, 1], arrpos[1, 2] + 0.05, 
     paste("P", "X", nrow(cor.x)+1," = ", round(Path$Residual, 2), sep=""), cex=0.6)

#Label path distance arrows
nr <- nrow(arrpos)
for(i in 2:nr){
  text(arrpos[i, 1], arrpos[i, 2] + 0.05, 
       paste("P", "X", i-1," = ", round(diag(Path$Coeff)[i-1], 2), sep=""), cex=0.6)
}

# Plot correlation arrows direction 1
nr <- nrow(fromto_CU)
arrpos <- matrix(ncol = 2, nrow = nr)
for (i in 1:nr)
  arrpos[i, ] <- curvedarrow (to = elpos[fromto_CU[i, 2], ],
                                from = elpos[fromto_CU[i, 1], ],
                                lwd = 2, arr.pos = 0.8, arr.length = 0.5, curve = 0.35)

# Plot correlation arrows - direction 2
nr <- nrow(fromto_CU)
arrpos <- matrix(ncol = 2, nrow = nr)
for (i in 1:nr)
  arrpos[i, ] <- curvedarrow (to = elpos[fromto_CU[i, 1], ],
                              from = elpos[fromto_CU[i, 2], ],
                              lwd = 2, arr.pos = 0.8, arr.length = 0.5, curve = -0.35)

# Create combinations of cor.x for labelling rxy in correlation arrows
rcomb <- as.data.frame(t(combn(seq(nrow(cor.x)),2)))
rcomb <- paste(rcomb$V1,rcomb$V2, sep="")

# Label correlation arrows
nr <- nrow(fromto_CU)
arrpos <- matrix(ncol = 2, nrow = nr)
for (i in 1:nr)
  arrpos[i, ] <- curvedarrow (to = elpos[fromto_CU[i, 1], ],
                              from = elpos[fromto_CU[i, 2], ],
                              lwd = 2, arr.pos = 0.5, lcol = "transparent", arr.length = 0.5, curve = -0.35)

nr <- nrow(arrpos)
for(i in 1:nr){
  text(arrpos[i, 1], arrpos[i, 2] + 0.05, 
       paste("r", "X", rcomb[i]," = ", round(as.dist(cor.x)[i], 2), sep=""), cex=0.6)
}

# Label Residual
textrect (elpos[1,], 0.09, 0.03,lab = "Residual", box.col = "white",
          shadow.col = "grey", shadow.size = 0.005, cex = 1)
# Label Dependent
textrect (elpos[2,], 0.09, 0.03,lab = attributes(y)$class, box.col = "white",
          shadow.col = "grey", shadow.size = 0.005, cex = 1)
# Label independents
nr <- nrow(elpos)
for (i in 3:nr){
  textrect (elpos[i,], 0.09, 0.03,lab = colnames(x)[i-2], box.col = "white",
            shadow.col = "grey", shadow.size = 0.005, cex = 1)
}

enter image description here

I need some help for

1) Plotting on a horizontal layout in diagram, so that the plot looks like the first one

2) Plotting subscripts in the arrow labels such as P_X5, r₁₂, r₃₄ etc. Combination of expression and paste in the loops used returns the indexing notation as such and not the indexed element.

Plotting Dewey and Lu path analysis results as a Path diagram in R

Answers (1)

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