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The robustness of maximum likelihood and distribution-free estimators to non-normality in confirmatory factor analysis
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Simulating Multivariate Nonnormal Distributions
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A Method for Simulating Non-Normal Distributions
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The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis
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Nonconvergence, Improper Solutions, and Starting Values in Lisrel Maximum Likelihood Estimation
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Issues in the Application of Covariance Structure Analysis: A Comment
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Robustness of Statistical Inference in Factor Analysis and Related Models
inferredcites →https://doi.org/10.1111/j.2044-8317.1984.tb00789.xopenalex-snapshot
Asymptotically distribution‐free methods for the analysis of covariance structures
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A comparison of some methodologies for the factor analysis of non‐normal Likert variables
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The Asymptotic Normal Distribution of Estimators in Factor Analysis under General Conditions
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On the Robustness of LISREL (Maximum Likelihood Estimation) Against Small Sample Size and Non-normality.
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