Developing multicomponent interventions using fractional factorial designs
dc.contributor.author | Chakraborty, Bibhas | en_US |
dc.contributor.author | Collins, Linda M. | en_US |
dc.contributor.author | Strecher, Victor J. | en_US |
dc.contributor.author | Murphy, Susan A. | en_US |
dc.date.accessioned | 2009-09-02T14:38:13Z | |
dc.date.available | 2010-10-05T18:27:29Z | en_US |
dc.date.issued | 2009-09-20 | en_US |
dc.identifier.citation | Chakraborty, 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.issn | 0277-6715 | en_US |
dc.identifier.issn | 1097-0258 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/63597 | |
dc.description.abstract | Multicomponent 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.extent | 182978 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | John Wiley & Sons, Ltd. | en_US |
dc.subject.other | Mathematics and Statistics | en_US |
dc.title | Developing multicomponent interventions using fractional factorial designs | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Medicine (General) | en_US |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | en_US |
dc.subject.hlbsecondlevel | Public Health | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department 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.affiliationum | Center for Health Communications Research, University of Michigan, Ann Arbor, MI, U.S.A. | en_US |
dc.contributor.affiliationum | Department of Statistics and The Institute for Social Research, University of Michigan, Ann Arbor, MI, U.S.A. | en_US |
dc.contributor.affiliationother | The Methodology Center and Department of Human Development and Family Studies, Pennsylvania State University, University Park, U.S.A. | en_US |
dc.identifier.pmid | 19575485 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/63597/1/3643_ftp.pdf | |
dc.identifier.doi | 10.1002/sim.3643 | en_US |
dc.identifier.source | Statistics in Medicine | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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