Stratification of Clinical Survey Data by Using Contingency Tables

摘要

Data stratification is the process of partitioning the data into distinct and non-overlapping groups since thestudy population consists of subpopulations that are of particular interest. In clinical data, once the data isstratified into sub populations based on a significant stratifying factor, different risk factors can bedetermined from each subpopulation. In this paper, the Fisher’s Exact Test is used to determine thesignificant stratifying factors. The experiments are conducted on a simulated study and the Medical,Epidemiological and Social Aspects of Aging (MESA) data constructed for prediction of urinaryincontinence. Results show that, smoking is the most significant stratifying factor of MESA data, showingthat the smokers and non-smokers indicates different risk factors towards urinary incontinence and shouldbe treated differently.