Combining Statistical Evidence From Several Studies

Rebecca M. Kuiper, Vincent Buskens, Werner Raub and Herbert Hoijtink

Sociological Methods & Research, 2013, vol. 42, issue 1, 60-81

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 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0049124112464867 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:42:y:2013:i:1:p:60-81

DOI: 10.1177/0049124112464867

Access Statistics for this article

More articles in Sociological Methods & Research
Bibliographic data for series maintained by SAGE Publications ().