Learn R Programming

BifactorIndicesCalculator (version 0.2.2)

cat_Omega_S: cat_Omega_S

Description

Computes an omega reliability estimate for all factors as described in Rodriguez, Reise, and Haviland (2016).

Usage

cat_Omega_S(Lambda, Thresh, Phi = NULL, Denom = NULL)

Arguments

Lambda

is a matrix of standardized factor loadings

Thresh

is a list (indexed by items) of vectors of item thresholds (items must be on a standardized metric).

Phi

is the latent variable covariance matrix. Defaults to NULL, and the identity matrix will be used. No other options are currently available.

Denom

specifies how the variance of the total score will be computed. Defaults to NULL, and the model implied total score variance will be used. No other options are currently available.

Value

A numeric, the omega reliability estimate for all factors using the technique of Green and Yang (2009).

Details

cat_Omega_S is called by bifactorIndices and the various convenience functions for exploratory models and/or Mplus output, which are the only functions in this package intended for casual users.

References

Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Evaluating bifactor models: calculating and interpreting statistical indices. Psychological Methods, 21(2), 137 10.1037/met0000045.

Green, S. B., & Yang, Y. (2009). Reliability of summed item scores using structural equation modeling: An alternative to coefficient alpha. Psychometrika, 74(1), 155-167 10.1007/s11336-008-9099-3.

See Also

Omega_H, bifactorIndices

Examples

Run this code
# NOT RUN {
Lambda <- matrix(c(.82, .10,   0,   0,
                   .77, .35,   0,   0,
                   .79, .32,   0,   0,
                   .66, .39,   0,   0,
                   .51,   0, .71,   0,
                   .56,   0, .43,   0,
                   .68,   0, .13,   0,
                   .60,   0, .50,   0,
                   .83,   0,   0, .47,
                   .60,   0,   0, .27,
                   .78,   0,   0, .28,
                   .55,   0,   0, .75),
                   ncol = 4, byrow = TRUE)
colnames(Lambda) <- c("General", "SF1", "SF2", "SF3")

Thresh = list(c(-1, 0, 1),  c(-0.5, 0, 0.5),
              c(0, 1, 2),   c(0, 0.5, 1),
              c(-2, -1, 0), c(-1, -0.5, 0),
              c(-1, 0, 2),  c(-0.5, 0, 1),
              c(-2, 0, 1),  c(-1, 0, 0.5),
              c(-1, 0, 1),  c(-0.5, 0, 0.5))

cat_Omega_S(Lambda, Thresh)

# }

Run the code above in your browser using DataLab