composite_d_scalar: Scalar formula to estimate the standardized mean difference...

View source: R/composites.R

composite_d_scalarR Documentation

Scalar formula to estimate the standardized mean difference associated with a composite variable


This function estimates the d value of a composite of X variables, given the mean d value of the individual X values and the mean correlation among those variables.


  p = 0.5,
  partial_intercor = FALSE



The mean standardized mean differences associated with variables in the composite to be formed.


The mean correlation among the variables in the composite.


The number of variables in the composite.


The proportion of cases in one of the two groups used the compute the standardized mean differences.


Logical scalar determining whether the intercor represents the partial (i.e., within-group) correlation among variables (TRUE) or the overall correlation between variables (FALSE).


There are two different methods available for computing such a composite, one that uses the partial intercorrelation among the X variables (i.e., the average within-group correlation) and one that uses the overall correlation among the X variables (i.e., the total or mixture correlation across groups).

If a partial correlation is provided for the interrelationships among variables, the following formula is used to estimate the composite d value:

d_composite = (mean_d * k_vars) / sqrt(mean_intercor * k_vars^2 + (1 - mean_intercor) * k_vars)

where d_composite is the composite d value, mean_d is the mean d value, mean_intercor is the mean intercorrelation among the variables in the composite, and k is the number of variables in the composite. Otherwise, the composite d value is computed by converting the mean d value to a correlation, computing the composite correlation (see composite_r_scalar for formula), and transforming that composite back into the d metric.


The estimated standardized mean difference associated with the composite variable.


Rosenthal, R., & Rubin, D. B. (1986). Meta-analytic procedures for combining studies with multiple effect sizes. Psychological Bulletin, 99(3), 400–406.


composite_d_scalar(mean_d = 1, mean_intercor = .7, k_vars = 2, p = .5)

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