path.analysis {agricolae} | R Documentation |

## Path Analysis

### Description

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.

### Usage

```
path.analysis(corr.x, corr.y)
```

### Arguments

`corr.x` |
Matrix of correlations of the independent variables |

`corr.y` |
vector of dependent correlations with each one of the independent ones |

### Details

It is necessary first to calculate the correlations.

### Value

Direct and indirect effects and residual Effect^2.

### Author(s)

Felipe de Mendiburu

### References

Biometrical Methods in Quantitative Genetic Analysis, Singh, Chaudhary. 1979

### See Also

### Examples

```
# 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)
```

[Package

*agricolae*version 1.3-7 Index]