Missing-Data Methods for Generalized Linear Models
Top Cited Papers
- 1 March 2005
- journal article
- Published by Taylor & Francis in Journal of the American Statistical Association
- Vol. 100 (469), 332-346
- https://doi.org/10.1198/016214504000001844
Abstract
Missing data is a major issue in many applied problems, especially in the biomedical sciences. We review four common approaches for inference in generalized linear models (GLMs) with missing covari...Keywords
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