Parallel Randomized Experiment: Difference between revisions
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=== 1981 === | === 1981 === | ||
* (Rubin, 1981) ⇒ Donald B. Rubin. (1981). “Estimation in parallel randomized experiments.” In: Journal of Educational and Behavioral Statistics, 6(4). | * (Rubin, 1981) ⇒ Donald B. Rubin. (1981). “Estimation in parallel randomized experiments.” In: Journal of Educational and Behavioral Statistics, 6(4). | ||
** Many studies comparing new treatments to standard treatments consist of [[Parallel Randomized Experiment|parallel randomized experiment]]s. In the example considered here, [[randomized experiment]]s 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 technique]]s that can be used to help summarize the evidence in such data about [[differences among | ** Many studies comparing new treatments to standard treatments consist of [[Parallel Randomized Experiment|parallel randomized experiment]]s. In the example considered here, [[randomized experiment]]s 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 technique]]s that can be used to help summarize the evidence in such data about [[differences among treatment]]s, 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. | ||
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Latest revision as of 04:36, 24 June 2024
A Parallel Randomized Experiment is a Randomized Experiment where experiment subjects are separated into MECE groups.
- …
- Counter-Example(s):
- See: Repeated Measures Randomized Experiment, Parallel Cluster Randomized Experiment.
References
1981
- (Rubin, 1981) ⇒ Donald B. Rubin. (1981). “Estimation in parallel randomized experiments.” In: Journal of Educational and Behavioral Statistics, 6(4).
- 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.