Literaturnachweis - Detailanzeige
| Autor/in | Zhang, Zhiyong |
|---|---|
| Titel | Modeling Error Distributions of Growth Curve Models through Bayesian Methods |
| Quelle | 48 (2016) 2, S.427-444 (18 Seiten)Infoseite zur Zeitschrift
PDF als Volltext (1); PDF als Volltext kostenfreie Datei (2) |
| Zusatzinformation | Weitere Informationen |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| DOI | 10.3758/s13428-015-0589-9 |
| Schlagwörter | Bayesian Statistics; Models; Statistical Distributions; Computation; Children; Longitudinal Studies; Surveys; Monte Carlo Methods; Markov Processes; Early Childhood Longitudinal Survey |
| Abstract | Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided. (As Provided). |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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