Generalized Linear Models in Biomedical Statistical Applications+
نویسندگان
چکیده
SUMMARY In biological assays, clinical trials, life-testing problems, reliability and survival analysis, and a variety of applied fields ranging from agrometry to biodivrersity to zodiacal sciences, generalized linear models covering usual linear, transformed linear, log-linear and nonlinear regression models, multi-nomial and logistic regression models, as well as some semiparametric ones, are potentially adoptable for drawing statistical conclusions from acquired data sets. Yet there may be some hidden barriers, originating from experimental as well as observational schemes, that merit careful examination in applications. Merits and demerits of generalized linear models in biomedical applications with due emphasis on their validity and robustness properties are thoroughly discussed.. .
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