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Alphainvesting: A procedure for sequential control of expected
, 2007
"... false discoveries ..."
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Recent developments towards optimality in multiple hypothesis testing
, 2006
"... There are many different notions of optimality even in testing a single hypothesis. In the multiple testing area, the number of possibilities is very much greater. The paper first will describe multiplicity issues that arise in tests involving a single parameter, and will describe a new optimality r ..."
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There are many different notions of optimality even in testing a single hypothesis. In the multiple testing area, the number of possibilities is very much greater. The paper first will describe multiplicity issues that arise in tests involving a single parameter, and will describe a new optimality result in that context. Although the example given is of minimal practical importance, it illustrates the crucial dependence of optimality on the precise specification of the testing problem. The paper then will discuss the types of expanded optimality criteria that are being considered when hypotheses involve multiple parameters, will note a few new optimality results, and will give selected theoretical references relevant to optimality considerations under these expanded criteria.
Empirical Bayes and fiducial effectsize estimation for small numbers of tests
, 2015
"... rate; selection bias; smallscale inference; Type II maximum likelihood ..."
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unknown title
, 2009
"... Multiple hypothesis testing on composite nulls using constrained pvalues ..."
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Multiple hypothesis testing on composite nulls using constrained pvalues
LARGESCALE SIMULTANEOUS INFERENCE WITH APPLICATIONS TO THE DETECTION OF DIFFERENTIAL EXPRESSION WITH MICROARRAY DATA
"... Often the first step, and indeed the major goal for many microarray studies, is the detection of genes that are differentially expressed in a known number of classes, C1,..., Cg. Statistical significance of differential expression can be tested by performing a test for each gene. When many hypothese ..."
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Often the first step, and indeed the major goal for many microarray studies, is the detection of genes that are differentially expressed in a known number of classes, C1,..., Cg. Statistical significance of differential expression can be tested by performing a test for each gene. When many hypotheses are tested, the probabil