How to Deal with Missing Categorical Data: Test of a Simple Bayesian Method
نویسندگان
چکیده
منابع مشابه
مقایسه روش بیزی (Bayesian) و کلاسیک در برآرد پارامترهای مدل رگرسیون لجستیک با وجود مقادیر گمشده در متغیرهای کمکی
Background and Aim: Logistic regression is an analytic tool widely used in medical and epidemiologic research. In many studies, we face data sets in which some of the data are not recorded. A simple way to deal with such "missing data" is to simply ignore the subjects with missing observations, and perform the analysis on cases for which complete data are available. Materials and Methods: We c...
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