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Interval estimation in multi-stage drop-the-losers designs.

Xiaomin Lu1, Ying He2, Samuel S Wu1

  • 11 Department of Biostatistics, University of Florida, Gainesville, FL, USA.

Statistical Methods in Medical Research
|March 17, 2016
PubMed
Summary

This study introduces a new conservative interval estimator for three-stage drop-the-losers designs. The proposed method offers improved efficiency and accuracy compared to existing bootstrap techniques for treatment effect estimation.

Keywords:
Clinical trialfamily-wise error rateinterval estimatemulti-arm multi-stage designstochastic order

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Area of Science:

  • Biostatistics
  • Clinical Trial Design

Background:

  • Drop-the-losers designs are adaptive clinical trial designs that sequentially drop underperforming treatment arms.
  • While two-stage designs are common, multi-stage designs, particularly three-stage, offer enhanced efficiency.
  • Estimating treatment effects and controlling error rates in complex multi-stage designs remains a challenge.

Purpose of the Study:

  • To develop and evaluate a novel interval estimator for treatment effect estimation in three-stage drop-the-losers designs.
  • To assess the statistical properties, including coverage probability and interval width, of the proposed estimator.
  • To ensure strong control of the family-wise error rate (FWER) under the global null hypothesis.

Main Methods:

  • Development of a conservative interval estimator based on stochastic ordering principles.
  • Theoretical proof of coverage probability using stochastic ordering.
  • Numerical simulations to compare the proposed estimator with existing bootstrap methods (Bowden and Glimm, 2014).

Main Results:

  • The proposed conservative interval estimator achieves at least the specified coverage probability.
  • Numerical results indicate narrower interval widths and higher coverage rates compared to the bootstrap method in most scenarios.
  • The stochastic ordering approach directly leads to strong control of the family-wise error rate.

Conclusions:

  • The proposed conservative interval estimator is a statistically sound and efficient method for three-stage drop-the-losers designs.
  • This approach offers advantages over existing bootstrap methods in terms of precision and accuracy.
  • The findings contribute to the advancement of adaptive clinical trial methodologies for improved treatment effect evaluation.