p-Value Adjustments for Asymptotic Control of the Generalized Familywise Error Rate
AbstractThis paper introduces a computationally efficient bootstrap procedure for obtaining multiplicity-adjusted p-values in situations where multiple hypotheses are tested simultaneously. This new testing procedure accounts for the mutual dependence of the individual statistics, and is shown under weak conditions to maintain asymptotic control of the generalized familywise error rate. Moreover, the estimated critical values (p-values) obtained via our procedure are less sensitive to the inclusion of true hypotheses and, as a result, our test has greater power to identify false hypotheses even as the collection of hypotheses under test increases in size. Another attractive feature of our test is that it leads naturally to balance among the individual hypotheses under test. This feature is especially attractive in settings where balance is desired but alternative approaches, such as those based on studentization, are difficult or infeasible.
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Bibliographic InfoPaper provided by Vanderbilt University Department of Economics in its series Vanderbilt University Department of Economics Working Papers with number 0905.
Date of creation: Apr 2009
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Web page: http://www.vanderbilt.edu/econ/wparchive/index.html
Bootstrap; familywise error; multiple testing; step-down; balanced testing;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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