Drosou, Krystallenia; Koukouvinos, Christos An information theoretical method for analyzing unreplicated designs with binary response. (English) Zbl 1436.62382 REVSTAT 17, No. 3, 383-399 (2019). Summary: The analysis of unreplicated factorial designs constitutes a challenging but difficult issue since there are no degrees of freedom so as to estimate the error variance. In the present paper we propose a method for screening active effects in such designs, assuming Bernoulli distributed data rather than linear; something that hasn’t received much attention yet. Specifically, we develop an innovating algorithm based on an information theoretical measure, the well-known symmetrical uncertainty, so that it can measure the relation between the response variable and each factor separately. The powerfulness of the proposed method is revealed via both, a thorough simulation study and a real data set analysis. MSC: 62K15 Factorial statistical designs 62J12 Generalized linear models (logistic models) 62R07 Statistical aspects of big data and data science 62P10 Applications of statistics to biology and medical sciences; meta analysis Keywords:two-level factorial designs; unreplicated experiments; generalized linear models; symmetrical uncertainty PDFBibTeX XMLCite \textit{K. Drosou} and \textit{C. Koukouvinos}, REVSTAT 17, No. 3, 383--399 (2019; Zbl 1436.62382) Full Text: Link