A Comparison of Different Nonnormal Distributions in Growth Mixture Models

Autor/inn/en	Son, Sookyoung; Lee, Hyunjung; Jang, Yoona; Yang, Junyeong; Hong, Sehee
Titel	A Comparison of Different Nonnormal Distributions in Growth Mixture Models
Quelle	In: Educational and Psychological Measurement, 79 (2019) 3, S.577-597 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164418823865
Schlagwörter	Statistical Distributions; Statistical Analysis; Structural Equation Models; Comparative Analysis; Sample Size; Statistical Bias; Differences + Suchen Sie Ihr Suchwort? Wahrscheinlichkeitsverteilung; Statistische Analyse; Unterscheiden
Abstract	The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew-t with equal skew and skew-t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with two different models: an unconditional GMM and a GMM with a continuous distal outcome variable. For the simulation, data were generated under the conditions of a different number of time points (4, 8), sample size (300, 800, 1,500), and skewness for intercept (1.2, 2, 4). Results demonstrate that it is not appropriate to fit nonnormal data to normal, t, or skew-normal distributions other than the skew-t distribution. It was also found that if there is skewness over time, it is necessary to model skewness in the slope as well. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01