coefficient_H: Coefficient H

In JonasMoss/reliable: Reliability Coefficients and Factor Scores for the Linear Factor Model

Description

Coefficient H is a optimal linearly weighted reliability coefficient for the congeneric measurement model. The function takes either a lavaan object or a list containing the matrix of factor loadings and the diagonal matrix of residual variances.

Usage

coefficient_H(object)

Arguments

object

Either a lavaan object or a list containing Lambda, the matrix of factor loadings, and Psi, a diagonal matrix of residual variances.

Details

The congeneric measurement model is the linear factor model with one latent variable, potentially different loadings, and a diagonal residual variance matrix. The congeneric reliability (see omega) is also a reliability under the congeneric measurement model. The difference between coefficient H and the congeneric reliability lies in the implied factor scores. While the congeneric reliability uses sum scores where each item in the scale is given the same weight, coefficient H uses best possible linear combination of the items in terms of squared error loss.

Value

A numeric containing the value of coefficient H.

References

Hancock, G. R. (2001). Rethinking construct reliability within latent variable systems. Structural equation modeling: Present and future, 195-216.

See Also

omega for the sum score reliability under the congeneric model when each score is 1. reliability for reliabilities under the linear factor model.

Examples

model <- " g =~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 "
fit <- lavaan::cfa(model = model, data = lavaan::HolzingerSwineford1939)
coefficient_H(fit)

JonasMoss/reliable documentation built on Nov. 18, 2019, 5:34 a.m.