title: Implementation of maximin efficient designs in dose-finding studies.
abstract: This paper considers the maximin approach for designing clinical studies. A maximin efficient design maximizes the smallest efficiency when compared with a standard design, as the parameters vary in a specified subset of the parameter space. To specify this subset of parameters in a real situation, a four-step procedure using elicitation based on expert opinions is proposed. Further, we describe why and how we extend the initially chosen subset of parameters to a much larger set in our procedure. By this procedure, the maximin approach becomes feasible for dose-finding studies. Maximin efficient designs have shown to be numerically difficult to construct. However, a new algorithm, the H-algorithm, considerably simplifies the construction of these designs. We exemplify the maximin efficient approach by considering a sigmoid Emax model describing a dose-response relationship and compare inferential precision with that obtained when using a uniform design. The design obtained is shown to be at least 15% more efficient than the uniform design.
authors.affiliation: Department of Statistics, Stockholm University, Stockholm, Sweden.
authors.forename: Ellinor
authors.initials: E
authors.lastname: Fackle-Fornius
authors.forename: Frank
authors.initials: F
authors.lastname: Miller
authors.forename: Hans
authors.initials: H
authors.lastname: Nyquist
mesh_terms: D004305:Dose-Response Relationship, Drug; D006801:Humans; D008962:Models, Theoretical; D012107:Research Design / Q000592:standards* / Q000706:statistics & numerical data
keywords: H-algorithm; clinical study; dose-response model; extension of parameter set; maximin efficient design; optimal design