View Item 

Show simple item record

Subgroup identification from randomized clinical trial data

dc.contributor.authorFoster, Jared C.en_US
dc.contributor.authorTaylor, Jeremy M. G.en_US
dc.contributor.authorRuberg, Stephen J.en_US
dc.date.accessioned2011-11-10T15:35:55Z
dc.date.available2012-12-03T21:17:30Zen_US
dc.date.issued2011-10-30en_US
dc.identifier.citationFoster, Jared C.; Taylor, Jeremy M.G.; Ruberg, Stephen J. (2011). "Subgroup identification from randomized clinical trial data." Statistics in Medicine 30(24): 2867-2880. <http://hdl.handle.net/2027.42/87004>en_US
dc.identifier.issn0277-6715en_US
dc.identifier.issn1097-0258en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/87004
dc.publisherJohn Wiley & Sons, Ltden_US
dc.subject.otherRandomized Clinical Trialsen_US
dc.subject.otherSubgroupsen_US
dc.subject.otherRandom Forestsen_US
dc.subject.otherRegression Treesen_US
dc.subject.otherTailored Therapeuticsen_US
dc.titleSubgroup identification from randomized clinical trial dataen_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.identifier.pmid21815180en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/87004/1/sim4322.pdf
dc.identifier.doi10.1002/sim.4322en_US
dc.identifier.sourceStatistics in Medicineen_US
dc.identifier.citedreferenceRuberg SJ, Chen L, Wang Y. The mean doesn't mean as much anymore: finding sub‐groups for tailored therapeutics. Clinical Trials 2010; 7: 574 – 583.en_US
dc.identifier.citedreferenceAssmann SF, Pocock SJ, Enos LE. Subgroup analysis and other (mis)uses of baseline data in clinical trials. The Lancet 2000; 355: 1064 – 1069.en_US
dc.identifier.citedreferenceBrookes ST, Whitley E, Peters TJ, Mulheran PA, Egger M, Smith GD. Subgroup analyses in randomized controlled trials: quantifying the risks of false‐positives and false‐negatives. Health Technology Assessment 2001; 5 ( 33 ): 1 – 56.en_US
dc.identifier.citedreferenceBrookes ST, Whitely E, Egger M, Smith GD, Mulheran PA, Peters TJ. Subgroup analyses in randomized trials: risks of subgroup‐specific analyses; power and sample size for the interaction test. Journal of Clinical Epidemiology 2004; 57: 229 – 236.en_US
dc.identifier.citedreferenceCui L, Hung HMJ, Wang SJ, Tsong Y. Issues related to subgroup analysis in clinical trials. Journal of Biopharmaceutical Statistics 2002; 12 ( 3 ): 347 – 358.en_US
dc.identifier.citedreferenceLagakos SW. The challenge of subgroup analyses—reporting without distorting. New England Journal of Medicine 2006; 354 ( 16 ): 1667 – 1669.en_US
dc.identifier.citedreferencePeto R, Collins R, Gray R. Large‐scale randomized evidence: large simple trials and overviews of trials. Journal of Clinical Epidemiology 1995; 48: 23 – 40.en_US
dc.identifier.citedreferencePocock SJ, Assmann SE, Enos LE, Kasten LE. Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Statistics in Medicine 2002; 21: 2917 – 2930.en_US
dc.identifier.citedreferenceRothwell PM. Subgroup analysis in randomized controlled trials: importance, indications and interpretation. The Lancet 2005; 365: 176 – 186.en_US
dc.identifier.citedreferenceYusuf S, Wittes J, Probstfield J, Tyroler HA. Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials. The Journal Of The American Medical Association 1991; 266 ( 1 ): 93 – 98.en_US
dc.identifier.citedreferenceWang R, Lagakos SW, Ware JH, Hunter DJ, Drazen JM. Statistics in medicine—reporting of subgroup analyses in clinical trials. New England Journal of Medicine 2007; 357 ( 21 ): 2189 – 2194.en_US
dc.identifier.citedreferenceFeinstein AR. The problem of cogent subgroups: a clinicostatistical tragedy. Journal of Clinical Epidemiology 1998; 51 ( 4 ): 297 – 299.en_US
dc.identifier.citedreferenceKehl V, Ulm K. Responder identification in clinical trials with censored data. Computational Statistics & Data Analysis 2006; 50 ( 5 ): 1338 – 1355. http://dx.doi.org/10.1016/j.csda.2004.11.015.en_US
dc.identifier.citedreferenceDixon DO, Simon R. Bayesian subset analysis. Biometrics 1991; 47: 871 – 881.en_US
dc.identifier.citedreferenceGail M, Simon R. Testing for qualitative interactions between treatment effects and patient subsets. Biometrics 1985; 41: 361 – 372.en_US
dc.identifier.citedreferenceSimon R. Bayesian subset analysis: application to studying treatment‐by‐gender interactions. Statistics in Medicine 2002; 21: 2909 – 2916.en_US
dc.identifier.citedreferenceNegassa A, Ciampi A, Abrahamowicz M, Shapiro S, Boivin JR. Tree‐structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria. Statistics and Computing 2005; 15: 231 – 239.en_US
dc.identifier.citedreferenceSu X, Tsai CL, Wang H, Nickerson DM, Bogong L. Subgroup analysis via recursive partitioning. The Journal of Machine Learning Research 2009; 10: 141 – 158.en_US
dc.identifier.citedreferenceSu X, Zhou T, Yan X, Fan J, Yang S. Interaction trees with censored survival data. The International Journal of Biostatistics 2008; 4 ( 1 ). Article 2.en_US
dc.identifier.citedreferenceFreidlin B, Jiang W, Simon R. The cross‐validated adaptive signature design. Clinical Cancer Research 2010; 16 ( 2 ): 691 – 698.en_US
dc.identifier.citedreferenceBreiman L. Random forests. Machine Learning 2001; 45 ( 1 ): 5 – 32.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Name:
sim4322.pdf
Size:
175.2KB
Format:
PDF
View/Open

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.