Does the Package Matter? A Comparison of Five Common Multilevel Modeling Software Packages

Autor/inn/en	McCoach, D. Betsy; Rifenbark, Graham G.; Newton, Sarah D.; Li, Xiaoran; Kooken, Janice; Yomtov, Dani; Gambino, Anthony J.; Bellara, Aarti
Titel	Does the Package Matter? A Comparison of Five Common Multilevel Modeling Software Packages
Quelle	In: Journal of Educational and Behavioral Statistics, 43 (2018) 5, S.594-627 (34 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (McCoach, D. Betsy)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998618776348
Schlagwörter	Hierarchical Linear Modeling; Computer Software; Comparative Analysis; Monte Carlo Methods; Accuracy; Error of Measurement; Computation; Efficiency; Computer Software Selection; Sample Size; Measurement Techniques; Usability + Suchen Sie Ihr Suchwort? Monte-Carlo-Methode; Messfehler; Effectiveness; Effektivität; Wirkungsgrad; Messtechnik
Abstract	This study compared five common multilevel software packages via Monte Carlo simulation: HLM 7, M"plus" 7.4, R (lme4 V1.1-12), Stata 14.1, and SAS 9.4 to determine how the programs differ in estimation accuracy and speed, as well as convergence, when modeling multiple randomly varying slopes of different magnitudes. Simulated data included population variance estimates, which were zero or near zero for two of the five random slopes. Generally, when yielding admissible solutions, all five software packages produced comparable and reasonably unbiased parameter estimates. However, noticeable differences among the five packages arose in terms of speed, convergence rates, and the production of standard errors for random effects, especially when the variances of these effects were zero in the population. The results of this study suggest that applied researchers should carefully consider which random effects they wish to include in their models. In addition, nonconvergence rates vary across packages, and models that fail to converge in one package may converge in another. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01