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Growth Mixture Modeling With Nonnormal Distributions: Implications for Data Transformation
This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased paramet...
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| Gepubliceerd in: | Educ Psychol Meas |
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| Hoofdauteurs: | , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
SAGE Publications
2020
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8243207/ https://ncbi.nlm.nih.gov/pubmed/34267397 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/0013164420976773 |
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