Literature DB >> 8922973

Adjusting for bias in C/E ratio estimates.

A A Stinnett.   

Abstract

The estimator used to calculate incremental cost-effectiveness (C/E) ratios from sampled data is biased but consistent. While the bias may be negligible in studies with large sample sizes, it is potentially important in analyses based on small samples. When patient-level data on costs and effects are available, bootstrap simulation methods can be used to estimate the bias of a C/E ratio and adjust the point estimate accordingly.

Entities:  

Mesh:

Year:  1996        PMID: 8922973     DOI: 10.1002/(SICI)1099-1050(199609)5:5<470::AID-HEC224>3.0.CO;2-5

Source DB:  PubMed          Journal:  Health Econ        ISSN: 1057-9230            Impact factor:   3.046


  5 in total

Review 1.  Advantages of using the net-benefit approach for analysing uncertainty in economic evaluation studies.

Authors:  Niklas Zethraeus; Magnus Johannesson; Bengt Jönsson; Mickael Löthgren; Magnus Tambour
Journal:  Pharmacoeconomics       Date:  2003       Impact factor: 4.981

Review 2.  Computed tomography screening for lung cancer in the National Lung Screening Trial: a cost-effectiveness analysis.

Authors:  William C Black
Journal:  J Thorac Imaging       Date:  2015-03       Impact factor: 3.000

3.  Cost-effectiveness of CT screening in the National Lung Screening Trial.

Authors:  William C Black; Ilana F Gareen; Samir S Soneji; JoRean D Sicks; Emmett B Keeler; Denise R Aberle; Arash Naeim; Timothy R Church; Gerard A Silvestri; Jeremy Gorelick; Constantine Gatsonis
Journal:  N Engl J Med       Date:  2014-11-06       Impact factor: 91.245

4.  Median-Based Incremental Cost-Effectiveness Ratio (ICER).

Authors:  Heejung Bang; Hongwei Zhao
Journal:  J Stat Theory Pract       Date:  2012-08-10

5.  Cost-efficacy comparison among three antiretroviral regimens in HIV-1 infected, treatment-experienced patients.

Authors:  Jörg Ruof; Alexander Dusek; Michael DeSpirito; Ralph A Demasi
Journal:  Clin Drug Investig       Date:  2007       Impact factor: 2.859

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.