# composite_d_matrix: Matrix formula to estimate the standardized mean difference... In psychmeta: Psychometric Meta-Analysis Toolkit

 composite_d_matrix R Documentation

## 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)
```

psychmeta documentation built on Aug. 26, 2022, 5:14 p.m.