Estimation in Parallel Randomized Experiments

Donald B. Rubin

Journal of Educational and Behavioral Statistics, 1981, vol. 6, issue 4, 377-401

Abstract: Many studies comparing new treatments to standard treatments consist of parallel randomized experiments. In the example considered here, randomized experiments were conducted in eight schools to determine the effectiveness of special coaching programs for the SAT. The purpose here is to illustrate Bayesian and empirical Bayesian techniques that can be used to help summarize the evidence in such data about differences among treatments, thereby obtaining improved estimates of the treatment effect in each experiment, including the one having the largest observed effect. Three main tools are illustrated: 1) graphical techniques for displaying sensitivity within an empirical Bayes framework, 2) simple simulation techniques for generating Bayesian posterior distributions of individual effects and the largest effect, and 3) methods for monitoring the adequacy of the Bayesian model specification by simulating the posterior predictive distribution in hypothetical replications of the same treatments in the same eight schools.

Keywords: Bayes estimation; coaching experiments; empirical Bayes estimation; simulation of posterior distributions; testing model adequacy (search for similar items in EconPapers)
Date: 1981
References: Add references at CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986006004377 (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:jedbes:v:6:y:1981:i:4:p:377-401

DOI: 10.3102/10769986006004377

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().