composite_d_matrix: Matrix formula to estimate the standardized mean difference...

In jadahlke/psychmeta: Psychometric Meta-Analysis Toolkit

Matrix formula to estimate the standardized mean difference associated with a weighted or unweighted composite variable

Description

This function is a wrapper for composite_r_matrix that converts d values to correlations, computes the composite correlation implied by the d values, and transforms the result back to the d metric.

Usage

composite_d_matrix(d_vec, r_mat, wt_vec, p = 0.5)

Arguments

d_vec	Vector of standardized mean differences associated with variables in the composite to be formed.
r_mat	Correlation matrix from which the composite is to be computed.
wt_vec	Weights to be used in forming the composite (by default, all variables receive equal weight).
p	The proportion of cases in one of the two groups used the compute the standardized mean differences.

Details

The composite d value is computed by converting the vector of d values to correlations, computing the composite correlation (see composite_r_matrix), and transforming that composite back into the d metric. See "Details" of composite_r_matrix for the composite computations.

Value

The estimated standardized mean difference associated with the composite variable.

Examples

composite_d_matrix(d_vec = c(1, 1), r_mat = matrix(c(1, .7, .7, 1), 2, 2),
                   wt_vec = c(1, 1), p = .5)

jadahlke/psychmeta documentation built on June 29, 2024, 5:43 a.m.