scholarly journals Sample Size Considerations in Clinical Trials When Comparing Two Interventions Using Multiple Co-Primary Binary Relative Risk Contrasts

2015 ◽  
Vol 7 (2) ◽  
pp. 81-94 ◽  
Author(s):  
Yuki Ando ◽  
Toshimitsu Hamasaki ◽  
Scott R. Evans ◽  
Koko Asakura ◽  
Tomoyuki Sugimoto ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Relative Risk ◽  
Sample Size

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.

Estimation of Bivariate Survival Function from Random Censored Data with Poisson Sample Size

2020 ◽  
Vol 72 (2) ◽  
pp. 111-121
Author(s):  
Abdurakhim Akhmedovich Abdushukurov ◽  
Rustamjon Sobitkhonovich Muradov
Keyword(s):  
Relative Risk ◽  
Sample Size ◽  
Censored Data ◽  
Survival Function ◽  
Survival Functions ◽  
Power Structures ◽  
Bivariate Survival ◽  
Empirical Estimates ◽  
Bivariate Survival Function ◽  
Product Limit

At the present time there are several approaches to estimation of survival functions of vectors of lifetimes. However, some of these estimators either are inconsistent or not fully defined in range of joint survival functions and therefore not applicable in practice. In this article, we consider three types of estimates of exponential-hazard, product-limit, and relative-risk power structures for the bivariate survival function, when replacing the number of summands in empirical estimates with a sequence of Poisson random variables. It is shown that these estimates are asymptotically equivalent. AMS 2000 subject classification: 62N01

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

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

scholarly journals Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications

2014 ◽  
Vol 56 (4) ◽  
pp. 614-630 ◽  
Author(s):  
Alexandra C. Graf ◽  
Peter Bauer ◽  
Ekkehard Glimm ◽  
Franz Koenig
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Error Rate ◽  
Type 1 Error ◽  
Multiarmed Clinical Trials

scholarly journals Sample Size Estimates for Clinical Trials of Vasospasm in Subarachnoid Hemorrhage

Stroke ◽  
2009 ◽  
Vol 40 (7) ◽  
pp. 2362-2367 ◽  
Author(s):  
Kurt T. Kreiter ◽  
Stephan A. Mayer ◽  
George Howard ◽  
Volker Knappertz ◽  
Don Ilodigwe ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Subarachnoid Hemorrhage ◽  
Sample Size ◽  
Size Estimates
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