psychmeta (version 2.3.4)

composite_d_matrix: 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.

Value

The estimated standardized mean difference associated with the composite variable.

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.

Examples

# NOT RUN {
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)
# }