How well does AIC perform in partially observed data? Keywords: Model selection, incomplete data, multiple imputation, AIC.
Many model selection criterions (e.g. AIC, BIC) proposed over the years have become common procedures in applied research. However, these procedures where designed for complete data. Complete data is rare in applied statistics, in particular in medical, public health and health policy settings. Incomplete data, another common problem is applied statistics, introduces its own set of complications in light of which the task of model selection can get quite complicated.
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