Literature DB >> 6630405

The relative efficiencies of matched and independent sample designs for case-control studies.

D C Thomas, S Greenland.   

Abstract

We have studied the asymptotic and small sample efficiencies of dependent (pair-matched or stratified) and independent samples as design techniques for case-control studies, and of matched, stratified, covariance-adjusted, and crude comparisons as methods of analysis. The asymptotic efficiencies of dependent sample designs relative to independent sample designs with adjustment were found to vary with the strengths of the relationships of disease with exposure and potential confounder: as the relationship with exposure increases, dependent samples lose efficiency; as the relationship with confounder increases, dependent samples gain efficiency. The relative efficiency also depends in a complicated manner on such other factors as the distribution of exposure and the strength of the exposure-confounder relationship. In the majority of situations examined, however, dependent samples were found to be somewhat more efficient than independent samples when confounding was present, while the reverse was true when confounding was absent. Results of small sample simulations do not differ importantly from the asymptotic results, except for pair-matching on a non-confounder, where the inefficiency of matching is greater in small samples.

Mesh:

Year:  1983        PMID: 6630405     DOI: 10.1016/0021-9681(83)90162-5

Source DB:  PubMed          Journal:  J Chronic Dis        ISSN: 0021-9681


  12 in total

1.  Invited commentary: understanding bias amplification.

Authors:  Judea Pearl
Journal:  Am J Epidemiol       Date:  2011-10-27       Impact factor: 4.897

2.  Matched designs and causal diagrams.

Authors:  Mohammad A Mansournia; Miguel A Hernán; Sander Greenland
Journal:  Int J Epidemiol       Date:  2013-06       Impact factor: 7.196

3.  An empirical investigation on matching in published case-control studies.

Authors:  O Gefeller; A Pfahlberg; H Brenner; J Windeler
Journal:  Eur J Epidemiol       Date:  1998-06       Impact factor: 8.082

4.  Biases introduced by choosing controls to match risk factors of cases in biomarker research.

Authors:  Margaret Sullivan Pepe; Jing Fan; Christopher W Seymour; Christopher Li; Ying Huang; Ziding Feng
Journal:  Clin Chem       Date:  2012-06-22       Impact factor: 8.327

5.  Empirical evaluation of sub-cohort sampling designs for risk prediction modeling.

Authors:  Myeonggyun Lee; Anne Zeleniuch-Jacquotte; Mengling Liu
Journal:  J Appl Stat       Date:  2020-12-21       Impact factor: 1.416

6.  Gray & white matter tissue contrast differentiates Mild Cognitive Impairment converters from non-converters.

Authors:  Angela L Jefferson; Katherine A Gifford; Stephen Damon; G William Chapman; Dandan Liu; Jamie Sparling; Vitaly Dobromyslin; David Salat
Journal:  Brain Imaging Behav       Date:  2015-06       Impact factor: 3.978

7.  Propensity score calibration in the absence of surrogacy.

Authors:  Mark Lunt; Robert J Glynn; Kenneth J Rothman; Jerry Avorn; Til Stürmer
Journal:  Am J Epidemiol       Date:  2012-04-24       Impact factor: 4.897

8.  Conducting density-sampled case-control studies using survey data with complex sampling designs: A simulation study.

Authors:  Catherine X Li; Ellicott C Matthay; Christopher Rowe; Patrick T Bradshaw; Jennifer Ahern
Journal:  Ann Epidemiol       Date:  2021-07-01       Impact factor: 3.797

9.  Matched Versus Unmatched Analysis of Matched Case-Control Studies.

Authors:  Fei Wan; Graham A Colditz; Siobhan Sutcliffe
Journal:  Am J Epidemiol       Date:  2021-09-01       Impact factor: 4.897

10.  Case-control matching: effects, misconceptions, and recommendations.

Authors:  Mohammad Ali Mansournia; Nicholas Patrick Jewell; Sander Greenland
Journal:  Eur J Epidemiol       Date:  2017-11-03       Impact factor: 12.434

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.