Analyzing Survival Data as Binary Outcomes with Logistic Regression Lim, Jo-Han; Lee, Kyeong-Eun; Hahn, Kyu-S.; Park, Kun-Woo;
Clinical researchers often analyze survival data as binary outcomes using the logistic regression method. This paper examines the information loss resulting from analyzing survival time as binary outcomes. We first demonstrate that, under the proportional hazard assumption, this binary discretization does result in a significant information loss. Second, when fitting a logistic model to survival time data, researchers inadvertently use the maximal statistic. We implement a numerical study to examine the properties of the reference distribution for this statistic, finally, we show that the logistic regression method can still be a useful tool for analyzing survival data in particular when the proportional hazard assumption is questionable.
Information loss;logistic regression;survival data;
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