On Muthen's Maximum Likelihood for Two-Level Covariance Structure Models

Autor/inn/en	Yuan, Ke-Hai; Hayashi, Kentaro
Titel	On Muthen's Maximum Likelihood for Two-Level Covariance Structure Models
Quelle	In: Psychometrika, 70 (2005) 1, S.147-167 (21 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
Schlagwörter	Sample Size; Behavioral Sciences; Maximum Likelihood Statistics; Statistical Analysis; Social Sciences; Data Collection; Evaluation Methods; Psychometrics + Suchen Sie Ihr Suchwort? Statistische Analyse; Social science; Sozialwissenschaften; Gesellschaftswissenschaften; Data capture; Datensammlung; Psychometry; Psychometrie
Abstract	Data in social and behavioral sciences are often hierarchically organized. Special statistical procedures that take into account the dependence of such observations have been developed. Among procedures for 2-level covariance structure analysis, Muthen's maximum likelihood (MUML) has the advantage of easier computation and faster convergence. When data are balanced, MUML is equivalent to the maximum likelihood procedure. Simulation results in the literature endorse the MUML procedure also for unbalanced data. This paper studies the analytical properties of the MUML procedure in general. The results indicate that the MUML procedure leads to correct model inference asymptotically when level-2 sample size goes to infinity and the coefficient of variation of the level-1 sample sizes goes to zero. The study clearly identifies the impact of level-1 and level-2 sample sizes on the standard errors and test statistic of the MUML procedure. Analytical results explain previous simulation results and will guide the design or data collection for the future applications of MUML. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10