Robertson, David S. and Choodari-Oskooei, Babak and Dimairo, Munya and Flight, Laura and Pallmann, Philip and Jaki, Thomas (2023) Point estimation for adaptive trial designs II: Practical considerations and guidance. STATISTICS IN MEDICINE, 42 (14). pp. 2496-2520. ISSN 0277-6715, 1097-0258
Full text not available from this repository. (Request a copy)Abstract
In adaptive clinical trials, the conventional end-of-trial point estimate of a treatment effect is prone to bias, that is, a systematic tendency to deviate from its true value. As stated in recent FDA guidance on adaptive designs, it is desirable to report estimates of treatment effects that reduce or remove this bias. However, it may be unclear which of the available estimators are preferable, and their use remains rare in practice. This article is the second in a two-part series that studies the issue of bias in point estimation for adaptive trials. Part I provided a methodological review of approaches to remove or reduce the potential bias in point estimation for adaptive designs. In part II, we discuss how bias can affect standard estimators and assess the negative impact this can have. We review current practice for reporting point estimates and illustrate the computation of different estimators using a real adaptive trial example (including code), which we use as a basis for a simulation study. We show that while on average the values of these estimators can be similar, for a particular trial realization they can give noticeably different values for the estimated treatment effect. Finally, we propose guidelines for researchers around the choice of estimators and the reporting of estimates following an adaptive design. The issue of bias should be considered throughout the whole lifecycle of an adaptive design, with the estimation strategy prespecified in the statistical analysis plan. When available, unbiased or bias-reduced estimates are to be preferred.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | SAMPLE-SIZE REESTIMATION; MAXIMUM-LIKELIHOOD-ESTIMATION; II/III CLINICAL-TRIALS; THE-LOSERS DESIGN; RANDOMIZED-TRIALS; CONDITIONAL ESTIMATION; HYPOTHESES SELECTION; SEQUENTIAL DESIGNS; ENRICHMENT DESIGNS; EARLY TERMINATION; adaptive design; bias-correction; conditional bias; point estimation; unconditional bias |
| Subjects: | 000 Computer science, information & general works > 004 Computer science |
| Divisions: | Informatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 16 Mar 2024 14:05 |
| Last Modified: | 16 Mar 2024 14:05 |
| URI: | https://pred.uni-regensburg.de/id/eprint/60216 |
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