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Abstract

The effect of an independent variable on a dependent variable is often evaluated with hypothesis testing. Sometimes, multiple studies are available that test the same hypothesis. In such studies, the dependent variable and the main predictors might differ, while they do measure the same theoretical concepts. In this article, we present a Bayesian updating method that can be used to quantify the joint evidence in multiple studies regarding the effect of one variable of interest. We apply our method to four studies on how trust in social and economic exchange depends on experience from previous exchange with the same partner. In addition, we examine five hypothetical situations in which the results from the separate studies are less clear-cut than in our trust example.

Keywords

Bayes factor Bayesian updating embeddedness posterior model probabilities trust

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Combining Statistical Evidence From Several Studies

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