# R/get_paths.r In plspm: Tools for Partial Least Squares Path Modeling (PLS-PM)

```#' @title Calculate path coefficients for \code{plspm}
#'
#' @details
#' Internal function. \code{get_paths} is called by \code{plspm}.
#'
#' @param path_matrix path matrix
#' @param Y_lvs Matrix of latent variables
#' @param full logical to indicate all results from 'summary(lm())'
#' @return list with inner results, path coefs matrix, R2, and residuals
#' @keywords internal
#' @template internals
#' @export
get_paths <-  function(path_matrix, Y_lvs, full=TRUE)
{
lvs_names = colnames(path_matrix)
endogenous = as.logical(rowSums(path_matrix))
num_endo = sum(endogenous)
results = as.list(1:num_endo)
Path = path_matrix
residuals = as.list(1:num_endo)
R2 = rep(0, nrow(path_matrix))

for (aux in 1:num_endo)
{
# index for endo LV
k1 <- which(endogenous)[aux]
# index for indep LVs
k2 = which(path_matrix[k1,] == 1)

path_lm = summary(lm(Y_lvs[,k1] ~ Y_lvs[,k2]))
Path[k1,k2] = path_lm\$coef[-1,1]
residuals[[aux]] = path_lm\$residuals
R2[k1] = path_lm\$r.squared
inn_val = c(path_lm\$r.squared, path_lm\$coef[,1])
# ----- NEW results
inn_labels = c("Intercept", names(k2))
rownames(path_lm\$coefficients) = inn_labels
results[[aux]] <- path_lm\$coefficients
# ----- OLD results
# inn_lab = c("R2", "Intercept",
# paste(rep("path_",length(k2)),names(k2),sep=""))
# names(inn_val) = NULL
# results[[aux]] <- data.frame(concept=inn_lab, value=round(inn_val, 4))
}
names(results) = lvs_names[endogenous]
names(R2) = lvs_names

# output
list(results, Path, R2, residuals)
}
```

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plspm documentation built on May 2, 2019, 7:05 a.m.