Description Usage Arguments Value Note Author(s) Examples
Find R2 given arbitrary predictor weights
1 | solveWtR2(r_mat, y_col, x_col, wt)
|
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.
This just calls solveWt() and squares the output.
Allen Goebl and Jeff Jones
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)
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