composite_rel_matrix | R Documentation |
This function computes the reliability of a variable that is a weighted or unweighted composite of other variables.
composite_rel_matrix(rel_vec, r_mat, sd_vec, wt_vec = rep(1, length(rel_vec)))
rel_vec |
Vector of reliabilities associated with variables in the composite to be formed. |
r_mat |
Correlation matrix from which the composite is to be computed. |
sd_vec |
Vector of standard deviations associated with variables in the composite to be formed. |
wt_vec |
Weights to be used in forming the composite (by default, all variables receive equal weight). |
This function treats measure-specific variance as reliable.
The Mosier composite formula is computed as:
\rho_{XX}=\frac{\mathbf{w}^{T}\left(\mathbf{r}\circ\mathbf{s}\right)+\mathbf{w}^{T}\mathbf{S}\mathbf{w}-\mathbf{w}^{T}\mathbf{s}}{\mathbf{w}^{T}\mathbf{S}\mathbf{w}}
where \rho_{XX}
is a composite reliability estimate, \mathbf{r}
is a vector of reliability estimates, \mathbf{w}
is a vector of weights, \mathbf{S}
is a covariance matrix, and \mathbf{s}
is a vector of variances (i.e., the diagonal elements of \mathbf{S}
).
The estimated reliability of the composite variable.
Mosier, C. I. (1943). On the reliability of a weighted composite. Psychometrika, 8(3), 161–168. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/BF02288700")}
Schmidt, F. L., & Hunter, J. E. (2015). Methods of meta-analysis: Correcting error and bias in research findings (3rd ed.). Thousand Oaks, CA: Sage. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.4135/9781483398105")}. pp. 441 - 447.
composite_rel_matrix(rel_vec = c(.8, .8),
r_mat = matrix(c(1, .4, .4, 1), 2, 2), sd_vec = c(1, 1))
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