dc.contributor.author David, Michael C dc.contributor.author Bensink, Mark dc.contributor.author Higashi, Hideki dc.contributor.author Donald, Maria dc.contributor.author Alati, Rosa dc.contributor.author Ware, Robert S dc.date.accessioned 2017-11-15T04:57:14Z dc.date.available 2017-11-15T04:57:14Z dc.date.issued 2012 dc.identifier.issn 0895-4356 dc.identifier.doi 10.1016/j.jclinepi.2012.04.013 dc.identifier.uri http://hdl.handle.net/10072/172330 dc.description.abstract Objective: To assess the cost-effectiveness of sample size maintenance programs in a prospective cohort. Study Design and Setting: The Living with Diabetes Study in Queensland, Australia is a longitudinal survey providing a comprehensive examination of health care utilization and disease progression among people with diabetes. Data from this study were used to compare the cost-effectiveness of a program incorporating substitution sampling with two alternative programs: “no follow-up” and “usual practice.” Results: A program involving substitution sampling was shown to be the most effective with an additional 3,556 complete responses (compared with a “no follow-up” program) and an additional 2,099 complete responses (compared with “usual practice”). An incremental analysis through a Monte Carlo simulation found substitution sampling to be the most cost-effective option for maintaining sample size with an incremental cost-effective ratio of $54.87 (95% uncertainty interval$52.68–$57.25) compared with$87.58 ($77.89–$100.09) for “usual practice.” Conclusions: Based on the available data, a program involving substitution sampling is economically justified and should be considered in any approach with the aim of maintaining sample size. There is, however, a continuing need to evaluate the effectiveness of this option on other outcome measures, such as bias. dc.description.peerreviewed Yes dc.language English dc.publisher Elsevier dc.relation.ispartofpagefrom 1200 dc.relation.ispartofpageto 1211 dc.relation.ispartofissue 11 dc.relation.ispartofjournal Journal of Clinical Epidemiology dc.relation.ispartofvolume 65 dc.subject.fieldofresearch Clinical Sciences not elsewhere classified dc.subject.fieldofresearch Mathematical Sciences dc.subject.fieldofresearch Medical and Health Sciences dc.subject.fieldofresearchcode 110399 dc.subject.fieldofresearchcode 01 dc.subject.fieldofresearchcode 11 dc.title Monte Carlo simulation of the cost-effectiveness of sample size maintenance programs revealed the need to consider substitution sampling dc.type Journal article dc.type.description C1 - Articles dc.type.code C - Journal Articles gro.hasfulltext No Full Text gro.griffith.author Ware, Robert gro.griffith.author David, Michael
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