The adoptr package

• Verfasst von: Kunzmann, Kevin [VerfasserIn]
• Verfasst von: Pilz, Maximilian [VerfasserIn]
• Verfasst von: Herrmann, Carolin [VerfasserIn]
• Verfasst von: Rauch, Geraldine [VerfasserIn]
• Verfasst von: Kieser, Meinhard [VerfasserIn]
• Titel: The adoptr package
• Titelzusatz: adaptive optimal designs for clinical trials in R
• Verf.angabe: Kevin Kunzmann, Maximilian Pilz, Carolin Herrmann, Geraldine Rauch, Meinhard Kieser
• E-Jahr: 2021
• Jahr: 2021-06-28
• Umfang: 21 S.
• Fussnoten: Gesehen am 20.09.2021
• Titel Quelle: Enthalten in: Journal of statistical software
• Ort Quelle: Los Angeles, Calif. : UCLA, Dept. of Statistics, 1996
• Jahr Quelle: 2021
• Band/Heft Quelle: 98(2021), 9, Seite 1-21
• ISSN Quelle: 1548-7660
• DOI: doi:10.18637/jss.v098.i09
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: clinical trials
• Sach-SW: optimal design
• Sach-SW: R
• K10plus-PPN: 1771040521

Abstract

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.