psychmeta (version 2.6.4)

var_error_mult_R: Estimate the error variance of linear regression multiple R(-squared)

Description

This function estimates the error variance for linear regression model (squared) multiple correlations (R and R^2R-squared).

Usage

var_error_mult_R(R, n, p)
var_error_mult_Rsq(Rsq, n, p)
var_error_R(R, n, p)
var_error_Rsq(Rsq, n, p)

Value

A vector of sampling-error variances.

Arguments

R

Vector of multiple correlation coefficients.

n

Vector of sample sizes.

p

Vector of numbers of predictors in the model.

Rsq

Vector of squared multiple correlation coefficients.

Details

The sampling variance of a multiple correlation is approximately:

var_e=(1-R^2)^2(n-p-1)^2(n^2-1)(n+3)var_e = (1 - R^2)^2 \* (n - p - 1)^2 / ((n^2 - 1) \* (n + 3))

The sampling variance of a squared multiple correlation is approximately:

var_e=4R^2(1-R^2)^2(n-p-1)^2(n^2-1)(n+3)var_e = 4 \* R^2 \* (1 - R^2)^2 \* (n - p - 1)^2 / ((n^2 - 1) \* (n + 3))

References

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Lawrence Erlbaum and Associates. tools:::Rd_expr_doi("10.4324/9780203774441"). p. 88.

Olkin, I., & Finn, J. D. (1995). Correlations redux. Psychological Bulletin, 118(1), 155–164. tools:::Rd_expr_doi("10.1037/0033-2909.118.1.155")

Examples

var_error_mult_R(R = .5, n = 30, p = 4)
var_error_mult_R(R = .5, n = 30, p = 4)
var_error_mult_Rsq(Rsq = .25, n = 30, p = 4)
var_error_mult_Rsq(Rsq = .25, n = 30, p = 4)