hancock: Obtain Hancock's H (CFA version of maximal reliability)

In eunscho/reliacoef: Compute and Compare Unidimensional and Multidimensional Reliability Coefficients

Obtain Hancock's H (CFA version of maximal reliability)

Description

It is the confirmatory factor analysis (CFA) version of maximal reliability. This coefficient takes the standardized factor loading as the reliability of each item, and finds the weight that maximizes the reliability. Hence, Hancock's H shows a different result than the reliability estimator using conventional unit weights.

Usage

hancock(x, nonneg_loading = FALSE)

Arguments

x	a dataframe or a cov (unidimensional)
nonneg_loading	if TRUE, constraint loadings to nonnegative values

Value

Hancock's H

References

Cho, E. (in press). Neither Cronbach's alpha nor McDonald's omega: A comment on Sijtsma and Pfadt. Psychometrika.

Hancock, G., & Mueller, R. O. (2001). Rethinking construct reliability within latent variable systems. In R. Cudeck, S. du Toit, & D. Sörbom (Eds.), Structural equation modeling: Present and future-A festschrift in honor of Karl Jöreskog (pp. 195-216). Scientific Software International.

Li, H., Rosenthal, R., & Rubin, D. B. (1996). Reliability of measurement in psychology: From Spearman-Brown to maximal reliability. Psychological Methods, 1(1), 98-107.

McNeish, D. (2017). Thanks coefficient alpha, we’ll take it from here. Psychological Methods, 23(3), 412-433.

Examples

hancock(Graham1)

eunscho/reliacoef documentation built on Jan. 30, 2023, 12:16 a.m.