Abstract Number:
3796
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Poster
Participants:
Tyson Rogers (1)
Institutions:
(1) NAMSA, Phoenix, AZ
First Author:
Presenting Author:
Abstract Text:
Medical device studies frequently present study design challenges due to the use of modest sample sizes and/or data distributions that differ from standard mathematical families of distributions. With increasing adoption of novel endpoints (e.g. hierarchical composites), statistical methods (e.g. restricted mean survival time for comparing time-to-event data), and complex adaptive designs, asymptotic formulas for sample size calculation and evaluation of operating characteristics are unavailable or unreliable. Simulation affords a practical and flexible method to optimize study design, through evaluation of the robustness of proposed statistical methods and sample size estimates. Similarly, in cases where pilot or feasibility study data is available, resampling methods may be employed to help evaluate the performance of planned statistical analysis methods and adequacy of sample size. This poster present examples of effective use of simulation and re-sampling based on recent experience with designing and reporting on medical device studies.
Keywords:
simulation|medical device|study design|conditional power|win ratio| restricted mean survival time
Sponsors:
Section on Medical Devices and Diagnostics
Tracks:
Study Design
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