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• W2167329809 abstract "The main objective in a group randomized trial is a comparison between treatments. Often, interest exists in the expected response for a particular group receiving a treatment. As a random sample of groups is included in the trial, the parameter for such a group is represented as a random effect. In this context, predicting the expected response for a group requires predicting a random effect. Proposed solutions to this problem are reviewed focusing on differences in the model assumptions in a simple setting. The author concludes that although popular computing solutions exist, fundamental open questions remain that impact interpretation.Keywords:mixed models;random effects;variance components;super-population models;model based;design based;Bayesian estimation;empirical Bayes" @default.
• W2167329809 created "2016-06-24" @default.
• W2167329809 creator A5067400392 @default.
• W2167329809 date "2014-09-29" @default.
• W2167329809 modified "2023-09-27" @default.
• W2167329809 title "Predicting Random Effects in Community Intervention" @default.
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• W2167329809 doi "https://doi.org/10.1002/9781118445112.stat07144" @default.
• W2167329809 hasPublicationYear "2014" @default.
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