Cited by 381Psychometric Methodologies and TestingStatistical Methods and Bayesian InferenceAdvanced Statistical Methods and Models

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Relative Performance of Categorical Diagonally Weighted Least Squares and Robust Maximum Likelihood Estimation

Bandalos, Deborah L.·2014·Structural Equation Modeling: A Multidisciplinary Journal

DOI 10.1080/10705511.2014.859510

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Abstract

Robust maximum likelihood (ML) and categorical diagonally weighted least squares (cat-DWLS) estimation have both been proposed for use with categorized and nonnormally distributed data. This study compares results from the 2 methods in terms of parameter estimate and standard error bias, power, and Type I error control, with unadjusted ML and WLS estimation methods included for purposes of comparison. Conditions manipulated include model misspecification, level of asymmetry, level and categorization, sample size, and type and size of the model. Results indicate that cat-DWLS estimation method results in the least parameter estimate and standard error bias under the majority of conditions studied. Cat-DWLS parameter estimates and standard errors were generally the least affected by model misspecification of the estimation methods studied. Robust ML also performed well, yielding relatively unbiased parameter estimates and standard errors. However, both cat-DWLS and robust ML resulted in low power under conditions of high data asymmetry, small sample sizes, and mild model misspecification. For more optimal conditions, power for these estimators was adequate.

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Authors: Bandalos, D. L.
Affiliations: James Madison University (US)
Corresponding author: Bandalos, Deborah L.
ORCID: Bandalos, Deborah L.
Venue: Structural Equation Modeling: A Multidisciplinary Journal
Publisher: Informa UK Limited
Published: 2014-01-02
Volume: 21
Issue: 1
Pages: 102-116
ISSN: 1070-5511 (ISSN-L)
1532-8007
DOI: 10.1080/10705511.2014.859510
OpenAlex: W2085399079
Cited by: 381
References: 25
Citations by year: 2026: 43 · 2025: 54 · 2024: 53 · 2023: 53 · 2022: 44 · 2021: 33 · 2020: 40 · 2019: 20 · 2018: 19 · 2017: 13 · 2016: 5 · 2015: 3 · 2014: 1
FWCI: 9.24
Type: journal article
Language: en
Open access: closed
Locations: Structural Equation Modeling A Multidisciplinary Journal (publishedVersion)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Keywords: categorical data, non-normal data, standard error bias, statistical power, type I error control, model misspecification, data asymmetry, sample size effects, weighted least squares

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Relative Performance of Categorical Diagonally Weighted Least Squares and Robust Maximum Likelihood Estimation

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