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An information theoretical method for analyzing unreplicated designs with binary response. (English) Zbl 1436.62382

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
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