Parameter accuracy in meta-analyses of factor structures

Autor(en): Gnambs, Timo
Staufenbiel, Thomas 
Stichwörter: bias; CORRELATION-COEFFICIENTS; CORRELATION-MATRICES; EXPLORATORY FACTOR-ANALYSIS; factor analysis; factor congruence; factor loadings; FACTOR PATTERN; FACTOR RECOVERY; Mathematical & Computational Biology; MAXIMUM-LIKELIHOOD; meta-analysis; MONTE-CARLO; Multidisciplinary Sciences; RANDOM-EFFECTS MODELS; ROTATION; SAMPLE-SIZE; Science & Technology - Other Topics
Erscheinungsdatum: 2016
Herausgeber: WILEY
Volumen: 7
Ausgabe: 2
Startseite: 168
Seitenende: 186
Two new methods for the meta-analysis of factor loadings are introduced and evaluated by Monte Carlo simulations. The direct method pools each factor loading individually, whereas the indirect method synthesizes correlation matrices reproduced from factor loadings. The results of the two simulations demonstrated that the accuracy of meta-analytical derived factor loadings is primarily affected by characteristics of the pooled factor structures (e.g., model error, communality) and to a lesser degree by the sample size of the primary studies and the number of included samples. The choice of the meta-analytical method had a minor impact. In general, the indirect method produced somewhat less biased estimates, particularly for small-sample studies. Thus, the indirect method presents a viable alternative for the meta-analysis of factor structures that could also address moderator hypotheses. Copyright (C) 2016 John Wiley & Sons, Ltd.
ISSN: 17592879
DOI: 10.1002/jrsm.1190

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