scholarly journals Improving sample size recalculation in adaptive clinical trials by resampling

2021 ◽  
Author(s):  
Carolin Herrmann ◽  
Corinna Kluge ◽  
Maximilian Pilz ◽  
Meinhard Kieser ◽  
Geraldine Rauch
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Adaptive Clinical Trials

Planning the Size of Clinical Trials with Allowance for Patient Noncompliance

1990 ◽  
Vol 29 (03) ◽  
pp. 243-246 ◽  
Author(s):  
M. A. A. Moussa
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Sample Size ◽  
Event Rate ◽  
Survival Functions ◽  
Time Intervals ◽  
Patient Noncompliance ◽  
Event Rates ◽  
Larger Sample

AbstractVarious approaches are considered for adjustment of clinical trial size for patient noncompliance. Such approaches either model the effect of noncompliance through comparison of two survival distributions or two simple proportions. Models that allow for variation of noncompliance and event rates between time intervals are also considered. The approach that models the noncompliance adjustment on the basis of survival functions is conservative and hence requires larger sample size. The model to be selected for noncompliance adjustment depends upon available estimates of noncompliance and event rate patterns.

scholarly journals Do patient characteristics matter when calculating sample size for eczema clinical trials?

2021 ◽  
Author(s):  
L. Howells ◽  
S. Gran ◽  
J. R. Chalmers ◽  
B. Stuart ◽  
M. Santer ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Patient Characteristics

scholarly journals A simple solution to the inadequacy of asymptotic likelihood-based inference for response-adaptive clinical trials

2021 ◽  
Author(s):  
Alessandro Baldi Antognini ◽  
Marco Novelli ◽  
Maroussa Zagoraiou
Keyword(s):  
Clinical Trials ◽  
Primary Outcome ◽  
Wald Test ◽  
Simple Solution ◽  
Nuisance Parameters ◽  
Simulation Studies ◽  
Fundamental Properties ◽  
Adaptive Clinical Trials ◽  
Treatment Comparisons ◽  
Practical Recommendations

AbstractThe present paper discusses drawbacks and limitations of likelihood-based inference in sequential clinical trials for treatment comparisons managed via Response-Adaptive Randomization. Taking into account the most common statistical models for the primary outcome—namely binary, Poisson, exponential and normal data—we derive the conditions under which (i) the classical confidence intervals degenerate and (ii) the Wald test becomes inconsistent and strongly affected by the nuisance parameters, also displaying a non monotonic power. To overcome these drawbacks, we provide a very simple solution that could preserve the fundamental properties of likelihood-based inference. Several illustrative examples and simulation studies are presented in order to confirm the relevance of our results and provide some practical recommendations.

Sample size calculation for clinical trials in which entry criteria and outcomes are counts of events

1994 ◽  
Vol 13 (8) ◽  
pp. 859-870 ◽  
Author(s):  
Robert P. McMahon ◽  
Michael Proschan ◽  
Nancy L. Geller ◽  
Peter H. Stone ◽  
George Sopko
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Sample Size Calculation
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