# solveWtR2: Find R2 given arbitrary predictor weights In iopsych: Methods for Industrial/Organizational Psychology

## Description

Find R2 given arbitrary predictor weights

## Usage

 `1` ```solveWtR2(r_mat, y_col, x_col, wt) ```

## Arguments

 `r_mat` A correlation matrix. `y_col` A vector of columns representing criterion variables. `x_col` A vector of columns representing predictor variables. `wt` A vector of predictor weights or a list of multiple vectors.

Regression R2.

## Note

This just calls solveWt() and squares the output.

## Author(s)

Allen Goebl and Jeff Jones

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```library(iopsych) #Get Data data(dls2007) r_mat <- dls2007[1:6, 2:7] #Get weights unit_wt <- c(1,1,1,1) other_wt <- c(1,2,1,.5) wt_list <- list(unit_wt, other_wt) #Solve solveWtR2(r_mat=r_mat, y_col=6, x_col=1:4, wt=unit_wt) solveWtR2(r_mat=r_mat, y_col=6, x_col=1:4, wt=other_wt) solveWtR2(r_mat=r_mat, y_col=6, x_col=1:4, wt=wt_list) ```

iopsych documentation built on May 2, 2019, 2:27 p.m.