The Effects of Autocorrelation on the Curve-of-Factors Growth Model

Autor/inn/en	Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.
Titel	The Effects of Autocorrelation on the Curve-of-Factors Growth Model
Quelle	In: Structural Equation Modeling: A Multidisciplinary Journal, 18 (2011) 3, S.430-448 (19 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1070-5511
Schlagwörter	Sample Size; Simulation; Factor Structure; Statistical Analysis; Statistics; Monte Carlo Methods; Evaluation; Error of Measurement; Correlation + Suchen Sie Ihr Suchwort? Simulation program; Simulationsprogramm; Faktorenstruktur; Statistische Analyse; Statistik; Monte-Carlo-Methode; Evaluierung; Messfehler; Korrelation
Abstract	This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a second model that included first-order autoregressive and moving average autocorrelation parameters. The results indicated that the estimates of the overall trend in the data were accurate regardless of model specification across most conditions. Variance components estimates were biased across many conditions but improved as sample size and series length increased. In general, the two models that incorporated autocorrelation parameters performed well when sample size and series length were large. The COFM had the best overall performance. (Contains 6 tables and 1 footnote.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10