로지스틱 모형에서 변수선택에 영향을 미치는 관측값에 대한 연구

Influential Observatyions on Variable Selection in Logistic Regression Model

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As is the case in linear regression, model fitting via logistic regression is also sensitive to influential cases. The values of statistic used for variable selection criteria can be reduced remarkably by excluding only a few influential cases. Furthermore, different subsets of explanatory variables change the influence patterns for the same response variable. Leger and Altman(1993) introduce a statistic, namely unconditional Cook’s distance, to assess the influence of each case on the variable selection procedure. We adopt same idea to logistic model and obtain an unconditional likelihood distance for the detection of influential cases. And some variable selection criteria for logistic model are also discussed.