Selection Effects in Meta-Analysis and Benefit Transfer: Avoiding Unintended Consequences
Selection effects include seemingly independent influences on, and choices in, conducting and reporting primary research that may bias a stock of knowledge. Such effects may arise from sociopolitical influences (research priority selection), researcher choices (methodology selection), peer review influences (publication selection), and meta-analyst choices (metadata sample selection). This paper discusses the impact, detection, and amelioration of selection effects within benefit transfer. Also discussed is evidence of selection effects in the literature and their implications for primary research. Evidence suggests that metaregression analysis may be the best tool for detecting and generating corrective measures for selection biases within benefit transfers.
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