The adoptr package: adaptive optimal designs for clinical trials in R
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-a...
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| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2021-06-28
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| In: |
Journal of statistical software
Year: 2021, Jahrgang: 98, Heft: 9, Pages: 1-21 |
| ISSN: | 1548-7660 |
| DOI: | 10.18637/jss.v098.i09 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.18637/jss.v098.i09 Verlag, lizenzpflichtig, Volltext: https://www.jstatsoft.org/index.php/jss/article/view/v098i09 
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| Verfasserangaben: | Kevin Kunzmann, Maximilian Pilz, Carolin Herrmann, Geraldine Rauch, Meinhard Kieser |
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| 520 | |a 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. | ||
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