2014/10/31 by Holger Dette, Dette, Holger, Katrin Kettelhake +3
Decision Sciences · Environmental Science · Mathematics · #Effects and risks of endocrine disrupting chemicals #FOS: Computer and information sciences #Methodology (stat.ME) #Optimal Experimental Design Methods #Statistical Methods in Clinical Trials #stat.ME
paper · pdf · doi:10.48550/arxiv.1410.8688
24 pages 3 figures
arxiv created 2014/10/31 · openalex publication_date 2014/10/31 · arxiv updated 2014/11/03 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
In a recent paper Dette et al. (2014) introduced optimal design problems for dose fnding studies with an active control. These authors concentrated on regression models with normal distributed errors (with known variance) and the problem of determining optimal designs for estimating the smallest dose, which achieves the same treatment effect as the active control. This paper discusses the problem of designing active-controlled dose fnding studies from a broader perspective. In particular, we consider a general class of optimality criteria and models arising from an exponential family, which are frequently used analyzing count data. We investigate under which circumstances optimal designs for dose fnding studies including a placebo can be used to obtain optimal designs for studies with an active control. Optimal designs are constructed for several situations and the differences arising from different distributional assumptions are investigated in detail. In particular, our results are applicable for constructing optimal experimental designs to analyze active-controlled dose fnding studies with discrete data, and we illustrate the efficiency of the new optimal designs with two recent examples from our consulting projects.