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• W2061144897 abstract "This article investigates maximum likelihood estimation with saturated and unsaturated models for correlated exchangeable binary data, when a sample of independent clusters of varying sizes is available. We discuss various parameterizations of these models, and propose using the EM algorithm to obtain maximum likelihood estimates. The methodology is illustrated by applications to a study of familial disease aggregation and to the design of a proposed group randomized cancer prevention trial." @default.
• W2061144897 created "2016-06-24" @default.
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• W2061144897 date "2003-03-01" @default.
• W2061144897 modified "2023-10-14" @default.
• W2061144897 title "Likelihood Inference for Exchangeable Binary Data with Varying Cluster Sizes" @default.
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• W2061144897 doi "https://doi.org/10.1111/1541-0420.00003" @default.
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