Literature DB >> 3961313

Choosing the number of controls in a matched case-control study, some sample size, power and efficiency considerations.

J M Taylor.   

Abstract

This paper investigates the efficiency of using multiple controls in a case-control study, when there is a single binary exposure variable. Specifically, we consider the asymptotic power of the Cochran test statistic against non-local alternatives of interest. When it is desirable to take multiple controls per case, we show that the marginal return rapidly diminishes as the number of controls per case increases. The effect is as strong, if not stronger, for non-local alternatives as it is for local alternatives. Hence, it is rarely worth choosing more than three controls per case. We also provide a table of sample sizes necessary to achieve 80 per cent power for some odds ratios not equal to one. We extend the results to a special case when there are two binary exposure variables.

Mesh:

Year:  1986        PMID: 3961313     DOI: 10.1002/sim.4780050106

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  23 in total

1.  Sample size evaluation for a multiply matched case-control study using the score test from a conditional logistic (discrete Cox PH) regression model.

Authors:  John M Lachin
Journal:  Stat Med       Date:  2008-06-30       Impact factor: 2.373

2.  Integration of Single-Center Data-Driven Vital Sign Parameters into a Modified Pediatric Early Warning System.

Authors:  Catherine E Ross; Iliana J Harrysson; Veena V Goel; Erika J Strandberg; Peiyi Kan; Deborah E Franzon; Natalie M Pageler
Journal:  Pediatr Crit Care Med       Date:  2017-05       Impact factor: 3.624

3.  Impact of measured total keratometry versus anterior keratometry on the refractive outcomes of the AT TORBI 709-MP toric intraocular lens.

Authors:  Antoine Levron; Hussam El Chehab; Emilie Agard; Roman Chudzinski; Jeremy Billant; Corinne Dot
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  2021-01-15       Impact factor: 3.117

4.  Cancer patients who refuse treatment.

Authors:  S A Huchcroft; T Snodgrass
Journal:  Cancer Causes Control       Date:  1993-05       Impact factor: 2.506

5.  Patterns of Health Care Usage in the Year Before Suicide: A Population-Based Case-Control Study.

Authors:  Megan M Chock; Tanner J Bommersbach; Jennifer L Geske; J Michael Bostwick
Journal:  Mayo Clin Proc       Date:  2015-10-09       Impact factor: 7.616

6.  ICU Telemedicine and Critical Care Mortality: A National Effectiveness Study.

Authors:  Jeremy M Kahn; Tri Q Le; Amber E Barnato; Marilyn Hravnak; Courtney C Kuza; Francis Pike; Derek C Angus
Journal:  Med Care       Date:  2016-03       Impact factor: 2.983

7.  A Simulation Study of Relative Efficiency and Bias in the Nested Case-Control Study Design.

Authors:  Stephen Bertke; Misty Hein; Mary Schubauer-Berigan; James Deddens
Journal:  Epidemiol Methods       Date:  2013-09

8.  Application of Behavioral Risk Factor Surveillance System Sampling Weights to Transgender Health Measurement.

Authors:  Ethan C Cicero; Sari L Reisner; Elizabeth I Merwin; Janice C Humphreys; Susan G Silva
Journal:  Nurs Res       Date:  2020 Jul/Aug       Impact factor: 2.381

9.  Exposure Enriched Case-Control (EECC) Design for the Assessment of Gene-Environment Interaction.

Authors:  Md Hamidul Huque; Raymond J Carroll; Nancy Diao; David C Christiani; Louise M Ryan
Journal:  Genet Epidemiol       Date:  2016-06-17       Impact factor: 2.135

10.  Deep Learning Systems for Pneumothorax Detection on Chest Radiographs: A Multicenter External Validation Study.

Authors:  Yee Liang Thian; Dianwen Ng; James Thomas Patrick Decourcy Hallinan; Pooja Jagmohan; Soon Yiew Sia; Cher Heng Tan; Yong Han Ting; Pin Lin Kei; Geoiphy George Pulickal; Vincent Tze Yang Tiong; Swee Tian Quek; Mengling Feng
Journal:  Radiol Artif Intell       Date:  2021-04-14
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.