V-optimality of designs in random effects Poisson regression models

Mehrdad Niaparast (), Sahar MehrMansour () and Rainer Schwabe ()
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Mehrdad Niaparast: Razi University
Sahar MehrMansour: Razi University
Rainer Schwabe: Otto-von-Guericke University

Metrika: International Journal for Theoretical and Applied Statistics, 2023, vol. 86, issue 8, No 2, 879-897

Abstract: Abstract The knowledge of the Fisher information is a fundamental tool to judge the quality of an experiment. Unlike in linear and generalized linear models without random effects, there is no closed form for the Fisher information in the situation of generalized linear mixed models, in general. To circumvent this problem, we make use of the quasi-information in this paper as an approximation to the Fisher information. We derive optimal designs based on the V-criterion, which aims to minimize the average variance of prediction of the mean response. For this criterion, we obtain locally optimal designs in two specific cases of a Poisson straight line regression model with either random intercepts or random slopes.

Keywords: Fisher information; Poisson regression; Quasi information; Random effects; V-optimality (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s00184-023-00896-3

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