Generalizations of the Familywise Error Rate
Consider the problem of simultaneously testing null hypotheses H1,..., Hs. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly...
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description | Consider the problem of simultaneously testing null hypotheses H1,..., Hs. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly if s is large, one might be willing to tolerate more than one false rejection provided the number of such cases is controlled, thereby increasing the ability of the procedure to detect false null hypotheses. This suggests replacing control of the FWER by controlling the probability of k or more false rejections, which we call the k-FWER. We derive both single-step and stepdown procedures that control the k-FWER, without making any assumptions concerning the dependence structure of the p-values of the individual tests. In particular, we derive a stepdown procedure that is quite simple to apply, and prove that it cannot be improved without violation of control of the k-FWER. We also consider the false discovery proportion (FDP) defined by the number of false rejections divided by the total number of rejections (defined to be 0 if there are no rejections). The false discovery rate proposed by Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300] controls E(FDP). Here, we construct methods such that, for any γ and α, $P{FDP>\gamma}\leq\alpha$. Two stepdown methods are proposed. The first holds under mild conditions on the dependence structure of p-values, while the second is more conservative but holds without any dependence assumptions. |
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In particular, we derive a stepdown procedure that is quite simple to apply, and prove that it cannot be improved without violation of control of the k-FWER. We also consider the false discovery proportion (FDP) defined by the number of false rejections divided by the total number of rejections (defined to be 0 if there are no rejections). The false discovery rate proposed by Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300] controls E(FDP). Here, we construct methods such that, for any γ and α, $P{FDP>\gamma}\leq\alpha$. Two stepdown methods are proposed. 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L.</creatorcontrib><creatorcontrib>Romano, Joseph P.</creatorcontrib><title>Generalizations of the Familywise Error Rate</title><title>The Annals of statistics</title><description>Consider the problem of simultaneously testing null hypotheses H1,..., Hs. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly if s is large, one might be willing to tolerate more than one false rejection provided the number of such cases is controlled, thereby increasing the ability of the procedure to detect false null hypotheses. This suggests replacing control of the FWER by controlling the probability of k or more false rejections, which we call the k-FWER. We derive both single-step and stepdown procedures that control the k-FWER, without making any assumptions concerning the dependence structure of the p-values of the individual tests. In particular, we derive a stepdown procedure that is quite simple to apply, and prove that it cannot be improved without violation of control of the k-FWER. We also consider the false discovery proportion (FDP) defined by the number of false rejections divided by the total number of rejections (defined to be 0 if there are no rejections). The false discovery rate proposed by Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300] controls E(FDP). Here, we construct methods such that, for any γ and α, $P{FDP>\gamma}\leq\alpha$. Two stepdown methods are proposed. The first holds under mild conditions on the dependence structure of p-values, while the second is more conservative but holds without any dependence assumptions.</description><subject>62G10</subject><subject>62J15</subject><subject>Error rates</subject><subject>Exact sciences and technology</subject><subject>Familywise error rate</subject><subject>Hypotheses</subject><subject>Hypothesis testing</subject><subject>Logical givens</subject><subject>Mathematical procedures</subject><subject>Mathematics</subject><subject>multiple testing</subject><subject>Multivariate analysis</subject><subject>Nonparametric inference</subject><subject>Null hypothesis</subject><subject>P values</subject><subject>p-value</subject><subject>Parametric inference</subject><subject>Probability and statistics</subject><subject>Sciences and techniques of general use</subject><subject>Statistics</subject><subject>stepdown procedure</subject><subject>Studies</subject><subject>Testing Methodology</subject><issn>0090-5364</issn><issn>2168-8966</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNplkFFLwzAQgIMoOKd_QHwogm9Wc2mSJm_K2KYwEMQ9h5ilmNI1M-mQ7deb0TIfvJeDu---Ow6ha8APQIA-YiwxKzhmuA9BT9CIABe5kJyfotEByBNBz9FFjHVCmKTFCN3PbWuDbtxed863MfNV1n3ZbKbXrtn9uGizaQg-ZO-6s5forNJNtFdDHqPlbPoxeckXb_PXyfMiN1SSLi8tqaQQlSgYgLUCG84Iq0BYqaUAKCnDUEKJS8KpBsMF4yshrOCf3BSFLMboqfdugq-t6ezWNG6lNsGtddgpr52aLBdDdUjaRwVAMCEUS5EUt0fF99bGTtV-G9p0tQLJJUmn8QSRHjLBxxhsdVwBWB3-qv7_NQ3dDWYdjW6qoFvj4t8klxySP3E3PVfHzodjv6BU8KT5BZ6Sfd8</recordid><startdate>20050601</startdate><enddate>20050601</enddate><creator>Lehmann, E. L.</creator><creator>Romano, Joseph P.</creator><general>Institute of Mathematical Statistics</general><general>The Institute of Mathematical Statistics</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope></search><sort><creationdate>20050601</creationdate><title>Generalizations of the Familywise Error Rate</title><author>Lehmann, E. L. ; Romano, Joseph P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c492t-7e2f988f83511ee80c6525f18e9a98117450171707264a1c6856d88e86b6c3393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>62G10</topic><topic>62J15</topic><topic>Error rates</topic><topic>Exact sciences and technology</topic><topic>Familywise error rate</topic><topic>Hypotheses</topic><topic>Hypothesis testing</topic><topic>Logical givens</topic><topic>Mathematical procedures</topic><topic>Mathematics</topic><topic>multiple testing</topic><topic>Multivariate analysis</topic><topic>Nonparametric inference</topic><topic>Null hypothesis</topic><topic>P values</topic><topic>p-value</topic><topic>Parametric inference</topic><topic>Probability and statistics</topic><topic>Sciences and techniques of general use</topic><topic>Statistics</topic><topic>stepdown procedure</topic><topic>Studies</topic><topic>Testing Methodology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lehmann, E. L.</creatorcontrib><creatorcontrib>Romano, Joseph P.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><jtitle>The Annals of statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lehmann, E. L.</au><au>Romano, Joseph P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Generalizations of the Familywise Error Rate</atitle><jtitle>The Annals of statistics</jtitle><date>2005-06-01</date><risdate>2005</risdate><volume>33</volume><issue>3</issue><spage>1138</spage><epage>1154</epage><pages>1138-1154</pages><issn>0090-5364</issn><eissn>2168-8966</eissn><coden>ASTSC7</coden><abstract>Consider the problem of simultaneously testing null hypotheses H1,..., Hs. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly if s is large, one might be willing to tolerate more than one false rejection provided the number of such cases is controlled, thereby increasing the ability of the procedure to detect false null hypotheses. This suggests replacing control of the FWER by controlling the probability of k or more false rejections, which we call the k-FWER. We derive both single-step and stepdown procedures that control the k-FWER, without making any assumptions concerning the dependence structure of the p-values of the individual tests. In particular, we derive a stepdown procedure that is quite simple to apply, and prove that it cannot be improved without violation of control of the k-FWER. We also consider the false discovery proportion (FDP) defined by the number of false rejections divided by the total number of rejections (defined to be 0 if there are no rejections). The false discovery rate proposed by Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300] controls E(FDP). Here, we construct methods such that, for any γ and α, $P{FDP>\gamma}\leq\alpha$. Two stepdown methods are proposed. The first holds under mild conditions on the dependence structure of p-values, while the second is more conservative but holds without any dependence assumptions.</abstract><cop>Hayward, CA</cop><pub>Institute of Mathematical Statistics</pub><doi>10.1214/009053605000000084</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 62G10 62J15 Error rates Exact sciences and technology Familywise error rate Hypotheses Hypothesis testing Logical givens Mathematical procedures Mathematics multiple testing Multivariate analysis Nonparametric inference Null hypothesis P values p-value Parametric inference Probability and statistics Sciences and techniques of general use Statistics stepdown procedure Studies Testing Methodology |
title | Generalizations of the Familywise Error Rate |
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