Literature DB >> 30250354

Hypothesis Tests for Neyman's Bias in Case-Control Studies.

D M Swanson1,2, C D Anderson3, R A Betensky2.   

Abstract

Survival bias is a long-recognized problem in case-control studies, and many varieties of bias can come under this umbrella term. We focus on one of them, termed Neyman's bias or "prevalence-incidence bias." It occurs in case-control studies when exposure affects both disease and disease-induced mortality, and we give a formula for the observed, biased odds ratio under such conditions. We compare our result with previous investigations into this phenomenon and consider models under which this bias may or may not be important. Finally, we propose three hypothesis tests to identify when Neyman's bias may be present in case-control studies. We apply these tests to three data sets, one of stroke mortality, another of brain tumors, and the last of atrial fibrillation, and find some evidence of Neyman's bias in the former two cases, but not the last case.

Entities:  

Keywords:  odds ratio; survival bias; truncation

Year:  2017        PMID: 30250354      PMCID: PMC6150474          DOI: 10.1080/02664763.2017.1401053

Source DB:  PubMed          Journal:  J Appl Stat        ISSN: 0266-4763            Impact factor:   1.404


  14 in total

1.  Statistics; servant of all sciences.

Authors:  J NEYMAN
Journal:  Science       Date:  1955-09-02       Impact factor: 47.728

2.  Event history analysis and the cross-section.

Authors:  Niels Keiding
Journal:  Stat Med       Date:  2006-07-30       Impact factor: 2.373

3.  Common carotid intima-media thickness and risk of stroke and myocardial infarction: the Rotterdam Study.

Authors:  M L Bots; A W Hoes; P J Koudstaal; A Hofman; D E Grobbee
Journal:  Circulation       Date:  1997-09-02       Impact factor: 29.690

4.  Global variation in stroke burden and mortality: estimates from monitoring, surveillance, and modelling.

Authors:  S Claiborne Johnston; Shanthi Mendis; Colin D Mathers
Journal:  Lancet Neurol       Date:  2009-02-21       Impact factor: 44.182

5.  Molecular subtypes of anaplastic oligodendroglioma: implications for patient management at diagnosis.

Authors:  Y Ino; R A Betensky; M C Zlatescu; H Sasaki; D R Macdonald; A O Stemmer-Rachamimov; D A Ramsay; J G Cairncross; D N Louis
Journal:  Clin Cancer Res       Date:  2001-04       Impact factor: 12.531

6.  Bias in analytic research.

Authors:  D L Sackett
Journal:  J Chronic Dis       Date:  1979

7.  Medications, comorbidities, and medical complications in stroke survivors: the CAReS study.

Authors:  Sharon K Ostwald; Joan Wasserman; Sally Davis
Journal:  Rehabil Nurs       Date:  2006 Jan-Feb       Impact factor: 1.625

8.  The effect of survival bias on case-control genetic association studies of highly lethal diseases.

Authors:  Christopher D Anderson; Michael A Nalls; Alessandro Biffi; Natalia S Rost; Steven M Greenberg; Andrew B Singleton; James F Meschia; Jonathan Rosand
Journal:  Circ Cardiovasc Genet       Date:  2011-02-03

Review 9.  Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review.

Authors:  Valery L Feigin; Carlene M M Lawes; Derrick A Bennett; Suzanne L Barker-Collo; Varsha Parag
Journal:  Lancet Neurol       Date:  2009-02-21       Impact factor: 44.182

10.  Analysis of a molecular genetic neuro-oncology study with partially biased selection.

Authors:  Rebecca A Betensky; David N Louis; J Gregory Cairncross
Journal:  Biostatistics       Date:  2003-04       Impact factor: 5.899

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