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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...

पूर्ण विवरण

में बचाया:
ग्रंथसूची विवरण
में प्रकाशित:Educ Psychol Meas
मुख्य लेखकों: Nam, Yeji, Hong, Sehee
स्वरूप: Artigo
भाषा:Inglês
प्रकाशित: SAGE Publications 2020
विषय:
ऑनलाइन पहुंच: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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