Ordinal measures in multiple indicator models: a simulation study of categorization error.

Using simulated data and a multiple indicator approach, examines the problems that surround categorization error. Results indicate that while categorization error does produce distortions in multiple indicator models, under most of the conditions explored, the bias was not sufficient to alter substantive interpretations and the estimates were efficient.-from Authors