Assessing the adequacy of the logistic regression model for matched case-control studies

We apply results for the detection of outliers in logistic regression to the analysis of matched pairs data and illustrate the techniques with data from a matched pairs study of the relationship between iron-binding proteins and mortality in the Solomon Islands. Although the study includes 90 matched pairs, the conclusions change substantially with deletion of one or two pairs. Thus, even with reasonably large data sets, single observations may have a great impact on the results of an analysis. The identification of influential observations should constitute part of the analysis of matched case-control data.