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Advances in Psychological Science    2012, Vol. 20 Issue (10) : 1538-1545     DOI: 10.3724/SP.J.1042.2012.01538
Conceptual Framework |
A Three-stage Integrative Model of Meta-analysis of Factor Analyses
FAN Hui-Yong;LIU Dong-Zhi;MA Yu-Hui;YIN Lang
School of Education and Sports Science & Institute of Educational Psychology, Bohai University, Jinzhou 121013, China
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Abstract  Meta-analysis of factor analysis (MAFA), also called meta-analytic factor analysis, integrated two methodological traditions namely meta analysis and factor analysis. Research on MAFA could explore some methodolical issues and accelerate the production process of psychological knowledge which will end the theoretical-principle-absence status of the meta analytic factor analysis had existed for several decades. To represent the process of MAFA, the present project put forth a three-stage integrative model under which some scientific questions will be tested using psychometrical methods including Monte Carlo simulation study. The validity of the three-stage integrative model and that of its data-synthesis methods (i.e. the co-occurrence matrix of salient factor loadings, the aggregate correlation matrix, and the pairwise rotation of results to congruence) were the key problems in this project. The project also planned to explore the general rules theoretically and steps of how to conducut MAFA study whose results would help the research community to use MAFA correctly. The possible scientific contribution of the present project is that it will add to the store of meta-analytic and factor analytic traditions, enrich the content of psychological methodology, and establish a solid base to popularize the MAFA.
Keywords meta-analysis of factor analysis      three-stage integrative model      meta analysis      factor analysis      Monte Carlo simulation     
Corresponding Authors: FAN Hui-Yong   
Issue Date: 23 October 2012
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FAN Hui-Yong
LIU Dong-Zhi
MA Yu-Hui
YIN Lang
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FAN Hui-Yong,LIU Dong-Zhi,MA Yu-Hui, et al. A Three-stage Integrative Model of Meta-analysis of Factor Analyses[J]. Advances in Psychological Science, 2012, 20(10): 1538-1545.
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