Prospective prediction in the presence of missing data.

Abstract

A variety of methods and algorithms are available for estimating parameters in the class of a generalized linear model in the presence of missing values. However, there is little information on how this already built model can be used for prediction in new observations with missing data in the covariates. Dropping the observations with missing values is a… (More)

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