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Developing multicomponent interventions using fractional factorial designs

dc.contributor.authorChakraborty, Bibhasen_US
dc.contributor.authorCollins, Linda M.en_US
dc.contributor.authorStrecher, Victor J.en_US
dc.contributor.authorMurphy, Susan A.en_US
dc.date.accessioned2009-09-02T14:38:13Z
dc.date.available2010-10-05T18:27:29Zen_US
dc.date.issued2009-09-20en_US
dc.identifier.citationChakraborty, Bibhas; Collins, Linda M.; Strecher, Victor J.; Murphy, Susan A. (2009). "Developing multicomponent interventions using fractional factorial designs." Statistics in Medicine 28(21): 2687-2708. <http://hdl.handle.net/2027.42/63597>en_US
dc.identifier.issn0277-6715en_US
dc.identifier.issn1097-0258en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/63597
dc.description.abstractMulticomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example, we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions. Copyright © 2009 John Wiley & Sons, Ltd.en_US
dc.format.extent182978 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherJohn Wiley & Sons, Ltd.en_US
dc.subject.otherMathematics and Statisticsen_US
dc.titleDeveloping multicomponent interventions using fractional factorial designsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMedicine (General)en_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Statistics and The Institute for Social Research, University of Michigan, Ann Arbor, MI, U.S.A. ; Department of Statistics, 439 West Hall, 1085 S. University Avenue, Ann Arbor, MI 48109-1107, U.S.A.en_US
dc.contributor.affiliationumCenter for Health Communications Research, University of Michigan, Ann Arbor, MI, U.S.A.en_US
dc.contributor.affiliationumDepartment of Statistics and The Institute for Social Research, University of Michigan, Ann Arbor, MI, U.S.A.en_US
dc.contributor.affiliationotherThe Methodology Center and Department of Human Development and Family Studies, Pennsylvania State University, University Park, U.S.A.en_US
dc.identifier.pmid19575485en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/63597/1/3643_ftp.pdf
dc.identifier.doi10.1002/sim.3643en_US
dc.identifier.sourceStatistics in Medicineen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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