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.

Bayes factor, Bayesian updating, embeddedness, posterior model probabilities, trust
dx.doi.org/10.1177/0049124112464867, hdl.handle.net/1765/83423
Sociological Methods and Research
Erasmus School of Law

Kuiper, R.M, Buskens, V.W, Raub, W, & Hoijtink, H. (2013). Combining Statistical Evidence From Several Studies: A Method Using Bayesian Updating and an Example From Research on Trust Problems in Social and Economic Exchange. Sociological Methods and Research, 42(1), 60–81. doi:10.1177/0049124112464867