Type-II generalized family-wise error rate formulas with application to sample size determination.
Identifieur interne : 001C43 ( PubMed/Curation ); précédent : 001C42; suivant : 001C44Type-II generalized family-wise error rate formulas with application to sample size determination.
Auteurs : Phillipe Delorme [Canada] ; Pierre Lafaye De Micheaux [Canada] ; Benoit Liquet [France] ; Jérémie Riou [France]Source :
- Statistics in medicine [ 1097-0258 ] ; 2016.
Abstract
Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd.
DOI: 10.1002/sim.6909
PubMed: 26914402
Links toward previous steps (curation, corpus...)
- to stream PubMed, to step Corpus: Pour aller vers cette notice dans l'étape Curation :001C67
Links to Exploration step
pubmed:26914402Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Type-II generalized family-wise error rate formulas with application to sample size determination.</title>
<author><name sortKey="Delorme, Phillipe" sort="Delorme, Phillipe" uniqKey="Delorme P" first="Phillipe" last="Delorme">Phillipe Delorme</name>
<affiliation wicri:level="1"><nlm:affiliation>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec, Canada.</nlm:affiliation>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="De Micheaux, Pierre Lafaye" sort="De Micheaux, Pierre Lafaye" uniqKey="De Micheaux P" first="Pierre Lafaye" last="De Micheaux">Pierre Lafaye De Micheaux</name>
<affiliation wicri:level="1"><nlm:affiliation>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec, Canada.</nlm:affiliation>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Liquet, Benoit" sort="Liquet, Benoit" uniqKey="Liquet B" first="Benoit" last="Liquet">Benoit Liquet</name>
<affiliation wicri:level="1"><nlm:affiliation>Laboratoire de Mathématiques et de leurs Applications, Université de Pau et des Pays de l'Adour, UMR CNRS, Pau, 5142, France.</nlm:affiliation>
<country xml:lang="fr">France</country>
<wicri:regionArea>Laboratoire de Mathématiques et de leurs Applications, Université de Pau et des Pays de l'Adour, UMR CNRS, Pau, 5142</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Riou, Jeremie" sort="Riou, Jeremie" uniqKey="Riou J" first="Jérémie" last="Riou">Jérémie Riou</name>
<affiliation wicri:level="1"><nlm:affiliation>Université d'Angers, INSERM, MINT, 1066, France.</nlm:affiliation>
<country xml:lang="fr">France</country>
<wicri:regionArea>Université d'Angers, INSERM, MINT, 1066</wicri:regionArea>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PubMed</idno>
<date when="2016">2016</date>
<idno type="RBID">pubmed:26914402</idno>
<idno type="pmid">26914402</idno>
<idno type="doi">10.1002/sim.6909</idno>
<idno type="wicri:Area/PubMed/Corpus">001C67</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">001C67</idno>
<idno type="wicri:Area/PubMed/Curation">001C43</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">001C43</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en">Type-II generalized family-wise error rate formulas with application to sample size determination.</title>
<author><name sortKey="Delorme, Phillipe" sort="Delorme, Phillipe" uniqKey="Delorme P" first="Phillipe" last="Delorme">Phillipe Delorme</name>
<affiliation wicri:level="1"><nlm:affiliation>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec, Canada.</nlm:affiliation>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="De Micheaux, Pierre Lafaye" sort="De Micheaux, Pierre Lafaye" uniqKey="De Micheaux P" first="Pierre Lafaye" last="De Micheaux">Pierre Lafaye De Micheaux</name>
<affiliation wicri:level="1"><nlm:affiliation>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec, Canada.</nlm:affiliation>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Liquet, Benoit" sort="Liquet, Benoit" uniqKey="Liquet B" first="Benoit" last="Liquet">Benoit Liquet</name>
<affiliation wicri:level="1"><nlm:affiliation>Laboratoire de Mathématiques et de leurs Applications, Université de Pau et des Pays de l'Adour, UMR CNRS, Pau, 5142, France.</nlm:affiliation>
<country xml:lang="fr">France</country>
<wicri:regionArea>Laboratoire de Mathématiques et de leurs Applications, Université de Pau et des Pays de l'Adour, UMR CNRS, Pau, 5142</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Riou, Jeremie" sort="Riou, Jeremie" uniqKey="Riou J" first="Jérémie" last="Riou">Jérémie Riou</name>
<affiliation wicri:level="1"><nlm:affiliation>Université d'Angers, INSERM, MINT, 1066, France.</nlm:affiliation>
<country xml:lang="fr">France</country>
<wicri:regionArea>Université d'Angers, INSERM, MINT, 1066</wicri:regionArea>
</affiliation>
</author>
</analytic>
<series><title level="j">Statistics in medicine</title>
<idno type="eISSN">1097-0258</idno>
<imprint><date when="2016" type="published">2016</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd.</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="In-Process" Owner="NLM"><PMID Version="1">26914402</PMID>
<DateCreated><Year>2016</Year>
<Month>06</Month>
<Day>06</Day>
</DateCreated>
<DateRevised><Year>2016</Year>
<Month>06</Month>
<Day>06</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1097-0258</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>35</Volume>
<Issue>16</Issue>
<PubDate><Year>2016</Year>
<Month>Jul</Month>
<Day>20</Day>
</PubDate>
</JournalIssue>
<Title>Statistics in medicine</Title>
<ISOAbbreviation>Stat Med</ISOAbbreviation>
</Journal>
<ArticleTitle>Type-II generalized family-wise error rate formulas with application to sample size determination.</ArticleTitle>
<Pagination><MedlinePgn>2687-714</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1002/sim.6909</ELocationID>
<Abstract><AbstractText>Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd.</AbstractText>
<CopyrightInformation>Copyright © 2016 John Wiley & Sons, Ltd.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Delorme</LastName>
<ForeName>Phillipe</ForeName>
<Initials>P</Initials>
<AffiliationInfo><Affiliation>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec, Canada.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>de Micheaux</LastName>
<ForeName>Pierre Lafaye</ForeName>
<Initials>PL</Initials>
<AffiliationInfo><Affiliation>Département de Mathématiques et de Statistique, Université de Montreal, 2920 Chemin de la Tour, Montréal, H3T 1J4, Québec, Canada.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>CREST-ENSAI, Campus de Ker-Lann, Rue Blaise Pascal, BP 37203, Bruz Cedex, 35172, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Liquet</LastName>
<ForeName>Benoit</ForeName>
<Initials>B</Initials>
<AffiliationInfo><Affiliation>Laboratoire de Mathématiques et de leurs Applications, Université de Pau et des Pays de l'Adour, UMR CNRS, Pau, 5142, France.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology (QUT), Brisbane, Australia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Riou</LastName>
<ForeName>Jérémie</ForeName>
<Initials>J</Initials>
<Identifier Source="ORCID">http://orcid.org/0000-0002-7056-9257</Identifier>
<AffiliationInfo><Affiliation>Université d'Angers, INSERM, MINT, 1066, France.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2016</Year>
<Month>02</Month>
<Day>23</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>England</Country>
<MedlineTA>Stat Med</MedlineTA>
<NlmUniqueID>8215016</NlmUniqueID>
<ISSNLinking>0277-6715</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">clinical research</Keyword>
<Keyword MajorTopicYN="N">multiple endpoints</Keyword>
<Keyword MajorTopicYN="N">multiple testing</Keyword>
<Keyword MajorTopicYN="N">r-power</Keyword>
<Keyword MajorTopicYN="N">sample size determination</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2015</Year>
<Month>04</Month>
<Day>21</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2016</Year>
<Month>01</Month>
<Day>13</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2016</Year>
<Month>01</Month>
<Day>16</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2016</Year>
<Month>2</Month>
<Day>26</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2016</Year>
<Month>2</Month>
<Day>26</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2016</Year>
<Month>2</Month>
<Day>26</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">26914402</ArticleId>
<ArticleId IdType="doi">10.1002/sim.6909</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Asie/explor/AustralieFrV1/Data/PubMed/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001C43 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Curation/biblio.hfd -nk 001C43 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Wicri/Asie |area= AustralieFrV1 |flux= PubMed |étape= Curation |type= RBID |clé= pubmed:26914402 |texte= Type-II generalized family-wise error rate formulas with application to sample size determination. }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Curation/RBID.i -Sk "pubmed:26914402" \ | HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Curation/biblio.hfd \ | NlmPubMed2Wicri -a AustralieFrV1
![]() | This area was generated with Dilib version V0.6.33. | ![]() |