R-optimal design strategies for logistic regression models with complementary log-log link
R-optimal design strategies for logistic regression models with complementary log-log link

Summary/Abstract: The manuscript explores optimal experimental design strategies, specifically R-optimality, for two-parameter logistic regression (2PLR) models using the complementary log-log (c-loglog) link function. The study seeks to establish efficient designs that minimize the average width of confidence bands across the range of p redictor variables. The general equivalence theorem validates the necessary and sufficient conditions of this optimality criterion.

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