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Optimal alpha spending for sequential analysis with binomial data
by
Silva, Ivair R.
, Yih, W. Katherine
, Kulldorff, Martin
in
Clinical trials
/ data analysis
/ Expected time to signal
/ Expenditures
/ Hypothesis testing
/ Linear programming
/ Original Articles
/ O’Brien–Fleming test
/ Pocock test
/ Power
/ Regression analysis
/ Safety surveillance
/ sample size
/ Sequential analysis
/ Statistical methods
/ Statistics
2020
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Optimal alpha spending for sequential analysis with binomial data
by
Silva, Ivair R.
, Yih, W. Katherine
, Kulldorff, Martin
in
Clinical trials
/ data analysis
/ Expected time to signal
/ Expenditures
/ Hypothesis testing
/ Linear programming
/ Original Articles
/ O’Brien–Fleming test
/ Pocock test
/ Power
/ Regression analysis
/ Safety surveillance
/ sample size
/ Sequential analysis
/ Statistical methods
/ Statistics
2020
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Do you wish to request the book?
Optimal alpha spending for sequential analysis with binomial data
by
Silva, Ivair R.
, Yih, W. Katherine
, Kulldorff, Martin
in
Clinical trials
/ data analysis
/ Expected time to signal
/ Expenditures
/ Hypothesis testing
/ Linear programming
/ Original Articles
/ O’Brien–Fleming test
/ Pocock test
/ Power
/ Regression analysis
/ Safety surveillance
/ sample size
/ Sequential analysis
/ Statistical methods
/ Statistics
2020
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Optimal alpha spending for sequential analysis with binomial data
Journal Article
Optimal alpha spending for sequential analysis with binomial data
2020
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Overview
For sequential analysis hypothesis testing, various alpha spending functions have been proposed. Given a prespecified overall alpha level and power, we derive the optimal alpha spending function that minimizes the expected time to signal for continuous as well as group sequential analysis. If there is also a restriction on the maximum sample size or on the expected sample size, we do the same. Alternatively, for fixed overall alpha, power and expected time to signal, we derive the optimal alpha spending function that minimizes the expected sample size. The method constructs alpha spending functions that are uniformly better than any other method, such as the classical Wald, Pocock or O’Brien–Fleming methods.The results are based on exact calculations using linear programming. All numerical examples were run by using the R Sequential package.
Publisher
Wiley,Oxford University Press
Subject
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