Abstract

DE ZAN, ARTURO T.. Experimental Sequential Designs for Logistic Regression Models. Rev.Colomb.Estad. [online]. 2008, vol.31, n.2, pp. 261-291. ISSN 0120-1751.

When the usual hypotheses of normality and constant variance do not hold (e.g. in binomial or Bernoulli processes), the problem of choosing appropriate designs creates problems to researches when pursuing a sequential exploration of process. This paper is based on De Zan (2006), where the author proposes two criteria to evaluate design strategies, that take the amount of information as the main evaluation tool. One into account the information of the fitted model, and the other explores the information that is contained on the approximation of a set of the best conditions of factors found on a fitted model. An example of how these strategies work is also given through a simulation using R software.

Keywords : Factorial Design; Response Surface Design; Sequential Design of Experiments; Generalized Linear Model; Logistic Regression; Fisher Information Matrix.