path.analysis {agricolae} | R Documentation |
If the cause and effect relationship is well defined, it is possible to represent the whole system of variables in a diagram form known as path-analysis. The function calculates the direct and indirect effects and uses the variables correlation or covariance.
path.analysis(corr.x, corr.y)
corr.x |
Matrix of correlations of the independent variables |
corr.y |
vector of dependent correlations with each one of the independent ones |
It is necessary first to calculate the correlations.
Direct and indirect effects and residual Effect^2.
Felipe de Mendiburu
Biometrical Methods in Quantitative Genetic Analysis, Singh, Chaudhary. 1979
# Path analysis. Multivarial Analysis. Anderson. Prentice Hall, pag 616 library(agricolae) # Example 1 corr.x<- matrix(c(1,0.5,0.5,1),c(2,2)) corr.y<- rbind(0.6,0.7) names<-c("X1","X2") dimnames(corr.x)<-list(names,names) dimnames(corr.y)<-list(names,"Y") path.analysis(corr.x,corr.y) # Example 2 # data of the progress of the disease related bacterial wilt to the ground # for the component CE Ca K2 Cu data(wilt) data(soil) x<-soil[,c(3,12,14,20)] y<-wilt[,14] cor.y<-correlation(y,x)$correlation cor.x<-correlation(x)$correlation path.analysis(cor.x,cor.y)