A Comparison of Diagonal Weighted Least Squares Robust Estimation Techniques for Ordinal Data
University of South Carolina · Baylor University
Abstract
AbstractThis study compared diagonal weighted least squares robust estimation techniques available in 2 popular statistical programs: diagonal weighted least squares (DWLS; LISREL version 8.80) and weighted least squares–mean (WLSM) and weighted least squares—mean and variance adjusted (WLSMV; Mplus version 6.11). A 20-item confirmatory factor analysis was estimated using item-level ordered categorical data. Three different nonnormality conditions were applied to 2- to 7-category data with sample sizes of 200, 400, and 800. Convergence problems were seen with nonnormal data when DWLS was used with few categories. Both DWLS and WLSMV produced accurate parameter estimates; however, bias in standard errors of…
Citation impact
- FWCI
- 8.73
- Percentile
- 100%
- References
- 32
Authors
2Topics & keywords
- Categorical variable
- Statistics
- Mathematics
- Estimator
- Diagonal
- Generalized least squares
- Least-squares function approximation
- LISREL