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A Taxonomy of Data Synthesis
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DOI：10.1177/01461672261451901.png)
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Abstract
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<jats:p>As efforts to improve the credibility of psychological and other social sciences continue, researchers aim to conduct multi-study or multi-sample research and synthesize findings using different parameterizations of individual participant meta-analysis. No overarching organizational framework exists, and only a few simulation-based or empirical examples comparing these parameterizations. This article has two goals. First, we provide an overview of six common parameterizations of individual participant meta-analysis, organized into a taxonomy based on different features (e.g., sample-specific parameters, meta-analytic parameters, and number of models). Second, using empirical data from 26,205 participants across 11 longitudinal studies, we provide comparisons of each parameterization testing prospective associations between the personality traits and crystallized abilities. We found that openness was a robust predictor of crystallized abilities across samples. Across methods, we observed consistency in model estimates, with some exceptions. We conclude with recommendations for choosing an approach given a team’s goals, questions, data availability, and model features.</jats:p>
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