  The relevance of determinacy coefficients as indicators for the validity of
factor score predictors has regularly been emphasized. Previous simulation
studies revealed biased determinacy coefficients for factor score predictors
based on categorical variables. Therefore, and because there are different
possibilities to compute determinacy coefficients, the present study compared
bias of determinacy coefficients for the best linear factor score predictor and
for a correlation-preserving factor score predictor based on confirmatory
factor models with observed variables with 2, 4, 6, and 8 categories and
maximum likelihood estimation, diagonally weighted least squares estimation,
and Bayesian estimation. Positive bias was found when data were based on
variables with two categories, population factors were correlated, and when
there were unmodeled cross-loadings. Based on the results, the correction for
sampling error, the use of maximum likelihood or Bayesian parameters, and data
with at least four categories are recommended to avoid overestimation of
parameter-based determinacy coefficients.
