Evaluating methods for handling missing ordinal data in structural equation modeling
Missing ordinal data are common in studies using structural equation modeling (SEM). Although several methods for dealing with missing ordinal data have been available, these methods often have not been systematically evaluated in SEM. In this study, we used Monte Carlo simulation to evaluate and co...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer New York LLC
2019
|
Subjects: | |
Online Access: | View Fulltext in Publisher |