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- W2262275308 abstract "Data augmentation is a technique for conducting approximate Bayesian regression analysis. This technique is a form of penalized likelihood estimation where prior information, represented by one or more specific prior data records, generates a penalty function that imposes the desired priors on the regression coefficients. We present a new command, penlogit, that fits penalized logistic regression via data augmentation. We illustrate the command through an example using data from an epidemiological study." @default.
- W2262275308 created "2016-06-24" @default.
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- W2262275308 date "2014-11-13" @default.
- W2262275308 modified "2023-10-02" @default.
- W2262275308 title "Approximate Bayesian logistic regression via penalized likelihood estimation with data augmentation" @default.
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