The adoptr Package: Adaptive Optimal Designs for Clinical Trials in R

被引：9

作者：

Kunzmann, Kevin ^{[1
]}

Pilz, Maximilian ^{[2
]}

Herrmann, Carolin ^{[3
,4
,5
,6
,7
]}

Rauch, Geraldine ^{[3
,4
,5
,6
,7
]}

Kieser, Meinhard ^{[2
]}

机构：

[1] Univ Cambridge, MRC Biostat Unit, Cambridge Inst Publ Hlth, Forvie Site,Robinson Way,Cambridge Biomed Campus, Cambridge CB2 0SR, England

[2] Heidelberg Univ, Inst Med Biometry & Informat, Neuenheimer Feld 130-3, D-69120 Heidelberg, Germany

[3] Charite Univ Med Berlin, Charitepl 1, D-10117 Berlin, Germany

[4] Free Univ Berlin, Charitepl 1, D-10117 Berlin, Germany

[5] Humboldt Univ, Charitepl 1, D-10117 Berlin, Germany

[6] Berlin Inst Hlth, Inst Biometry & Clin Epidemiol, Charitepl 1, D-10117 Berlin, Germany

[7] Berlin Inst Hlth BIH, Anna Louisa Karsch Str 2, D-10178 Berlin, Germany

来源：

JOURNAL OF STATISTICAL SOFTWARE | 2021年 / 98卷 / 09期

关键词：

optimal design; clinical trials; R;

D O I：

10.18637/jss.v098.i09

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Even though adaptive two-stage designs with unblinded interim analyses are becoming increasingly popular in clinical trial designs, there is a lack of statistical software to make their application more straightforward. The package adoptr fills this gap for the common case of two-stage one- or two-arm trials with (approximately) normally distributed outcomes. In contrast to previous approaches, adoptr optimizes the entire design upfront which allows maximal efficiency. To facilitate experimentation with different objective functions, adoptr supports a flexible way of specifying both (composite) objective scores and (conditional) constraints by the user. Special emphasis was put on providing measures to aid practitioners with the validation process of the package.

引用

页码：1 / 21

页数：21

共 46 条

[1]

[Anonymous], 2014, PRACTICAL CONSIDERAT, DOI DOI 10.1007/978-1-4939-1100-4_8

[2]

[Anonymous], 2007, REFL PAP METH ISS CO

[3] EVALUATION OF EXPERIMENTS WITH ADAPTIVE INTERIM ANALYSES [J].