Combining Statistical Evidence From Several Studies: A Method Using Bayesian Updating and an Example From Research on Trust Problems in Social and Economic Exchange

被引:19
|
作者
Kuiper, Rebecca M. [1 ]
Buskens, Vincent [2 ,3 ]
Raub, Werner [2 ]
Hoijtink, Herbert [1 ]
机构
[1] Univ Utrecht, Dept Methods & Stat, NL-3508 TC Utrecht, Netherlands
[2] Univ Utrecht, Dept Sociol ICS, NL-3508 TC Utrecht, Netherlands
[3] Erasmus Univ, Erasmus Sch Law, Rotterdam, Netherlands
关键词
Bayes factor; Bayesian updating; embeddedness; posterior model probabilities; trust; EMBEDDEDNESS; LIKELIHOOD;
D O I
10.1177/0049124112464867
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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.
引用
收藏
页码:60 / 81
页数:22
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