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Synthesizing Indirect Effects in Mediation Models With Meta-Analytic Methods
In: Alcohol and alcoholism: the international journal of the Medical Council on Alcoholism (MCA) and the journal of the European Society for Biomedical Research on Alcoholism (ESBRA), Band 57, Heft 1, S. 5-15
ISSN: 1464-3502
AbstractAimsA mediator is a variable that explains the underlying mechanism between an independent variable and a dependent variable. The indirect effect indicates the effect from the predictor to the outcome variable via the mediator. In contrast, the direct effect represents the predictor's effort on the outcome variable after controlling for the mediator.MethodsA single study rarely provides enough evidence to answer research questions in a particular domain. Replications are generally recommended as the gold standard to conduct scientific research. When a sufficient number of studies have been conducted addressing similar research questions, a meta-analysis can be used to synthesize those studies' findings.ResultsThe main objective of this paper is to introduce two frameworks to integrating studies using mediation analysis. The first framework involves calculating standardized indirect effects and direct effects and conducting a multivariate meta-analysis on those effect sizes. The second one uses meta-analytic structural equation modeling to synthesize correlation matrices and fit mediation models on the average correlation matrix. We illustrate these procedures on a real dataset using the R statistical platform.ConclusionThis paper closes with some further directions for future studies.
Applied Meta-Analysis for Social Science Research by N. A. Card
In: Structural equation modeling: a multidisciplinary journal, Band 20, Heft 4, S. 704-707
ISSN: 1532-8007
Multivariate Meta-Analysis as Structural Equation Models
In: Structural equation modeling: a multidisciplinary journal, Band 20, Heft 3, S. 429-454
ISSN: 1532-8007
Implementing Restricted Maximum Likelihood Estimation in Structural Equation Models
In: Structural equation modeling: a multidisciplinary journal, Band 20, Heft 1, S. 157-167
ISSN: 1532-8007
Constructing Approximate Confidence Intervals for Parameters With Structural Equation Models
In: Structural equation modeling: a multidisciplinary journal, Band 16, Heft 2, S. 267-294
ISSN: 1532-8007
A Direct Estimation Method on Analyzing Ipsative Data With Chan and Bentler's (1993) Method
In: Structural equation modeling: a multidisciplinary journal, Band 11, Heft 2, S. 217-243
ISSN: 1532-8007
A Commentary on Lv and Maeda (2019)
In: Structural equation modeling: a multidisciplinary journal, Band 27, Heft 3, S. 438-441
ISSN: 1532-8007
Applications of Multilevel Structural Equation Modeling to Cross-Cultural Research
In: Structural equation modeling: a multidisciplinary journal, Band 12, Heft 4, S. 598-619
ISSN: 1532-8007
Reducing Uniform Response Bias With Ipsative Measurement in Multiple-Group Confirmatory Factor Analysis
In: Structural equation modeling: a multidisciplinary journal, Band 9, Heft 1, S. 55-77
ISSN: 1532-8007
A Study of Sexual Satisfaction and Frequency of Sex Among Hong Kong Chinese Couples
In: The Journal of sex research, Band 45, Heft 2, S. 129-139
ISSN: 1559-8519