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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...

Täydet tiedot

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Bibliografiset tiedot
Julkaisussa:Educ Psychol Meas
Päätekijät: Nam, Yeji, Hong, Sehee
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: SAGE Publications 2020
Aiheet:
Linkit: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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