adjust_Rsq: Adjust a regression model R-squared for overfitting

In configural: Multivariate Profile Analysis

Description

Estimate shrinkage for regression models

Usage

adjust_Rsq(Rsq, n, p, adjust = c("fisher", "pop", "cv"))

Arguments

Rsq	Observed model R-squared
n	Sample size
p	Number of predictors
adjust	Which adjustment to apply. Options are "fisher" for the Adjusted R-squared method used in stats::lm(), "pop" for the positive-part Pratt estimator of the population R-squared, and "cv" for the Browne/positive-part Pratt estimator of the cross-validity R-squared. Based on Shieh (2008), these are the estimators for the population and cross-validity R-squared values that show the least bias with a minimal increase in computational complexity.

Value

An adjusted R-squared value.

References

Shieh, G. (2008). Improved shrinkage estimation of squared multiple correlation coefficient and squared cross-validity coefficient. Organizational Research Methods, 11(2), 387–407. doi: 10.1177/1094428106292901

Examples

adjust_Rsq(.55, 100, 6, adjust = "pop")

configural documentation built on Jan. 19, 2021, 1:06 a.m.