Literature DB >> 28535177

Invited Commentary: Selection Bias Without Colliders.

Miguel A Hernán.   

Abstract

In causal analyses, conditioning on a collider generally results in selection bias. Conditioning on a prognostic factor that is independent of the exposure-and therefore is not a collider-can also result in selection bias when 1) the exposure has a non-null effect on the outcome and 2) the association between the noncollider and the outcome is heterogenous across levels of the exposure. This result was empirically demonstrated by Greenland in 1977 (Am J Epidemiol. 1977;106(3):184-187).
© The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Keywords:  causal diagrams; collider; loss to follow-up; selection bias

Mesh:

Year:  2017        PMID: 28535177      PMCID: PMC6664806          DOI: 10.1093/aje/kwx077

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  28 in total

1.  Can Survival Bias Explain the Age Attenuation of Racial Inequalities in Stroke Incidence?: A Simulation Study.

Authors:  Elizabeth Rose Mayeda; Hailey R Banack; Kirsten Bibbins-Domingo; Adina Zeki Al Hazzouri; Jessica R Marden; Rachel A Whitmer; M Maria Glymour
Journal:  Epidemiology       Date:  2018-07       Impact factor: 4.822

2.  Methodological Challenges When Studying Distance to Care as an Exposure in Health Research.

Authors:  Ellen C Caniglia; Rebecca Zash; Sonja A Swanson; Kathleen E Wirth; Modiegi Diseko; Gloria Mayondi; Shahin Lockman; Mompati Mmalane; Joseph Makhema; Scott Dryden-Peterson; Kalé Z Kponee-Shovein; Oaitse John; Eleanor J Murray; Roger L Shapiro
Journal:  Am J Epidemiol       Date:  2019-09-01       Impact factor: 4.897

3.  Diagnosing Covariate Balance Across Levels of Right-Censoring Before and After Application of Inverse-Probability-of-Censoring Weights.

Authors:  John W Jackson
Journal:  Am J Epidemiol       Date:  2019-12-31       Impact factor: 4.897

4.  When Is a Complete-Case Approach to Missing Data Valid? The Importance of Effect-Measure Modification.

Authors:  Rachael K Ross; Alexander Breskin; Daniel Westreich
Journal:  Am J Epidemiol       Date:  2020-12-01       Impact factor: 4.897

5.  Target Validity and the Hierarchy of Study Designs.

Authors:  Daniel Westreich; Jessie K Edwards; Catherine R Lesko; Stephen R Cole; Elizabeth A Stuart
Journal:  Am J Epidemiol       Date:  2019-02-01       Impact factor: 4.897

6.  Does selective survival before study enrolment attenuate estimated effects of education on rate of cognitive decline in older adults? A simulation approach for quantifying survival bias in life course epidemiology.

Authors:  Elizabeth Rose Mayeda; Teresa J Filshtein; Yorghos Tripodis; M Maria Glymour; Alden L Gross
Journal:  Int J Epidemiol       Date:  2018-10-01       Impact factor: 7.196

7.  How subgroup analyses can miss the trees for the forest plots: A simulation study.

Authors:  Michael Webster-Clark; John A Baron; Michele Jonsson Funk; Daniel Westreich
Journal:  J Clin Epidemiol       Date:  2020-06-19       Impact factor: 6.437

8.  Diagnostic Assessment of Assumptions for External Validity: An Example Using Data in Metastatic Colorectal Cancer.

Authors:  Michael A Webster-Clark; Hanna K Sanoff; Til Stürmer; Sharon Peacock Hinton; Jennifer L Lund
Journal:  Epidemiology       Date:  2019-01       Impact factor: 4.822

9.  Survival-related Selection Bias in Studies of Racial Health Disparities: The Importance of the Target Population and Study Design.

Authors:  Chanelle J Howe; Whitney R Robinson
Journal:  Epidemiology       Date:  2018-07       Impact factor: 4.822

10.  Selection Bias When Estimating Average Treatment Effects Using One-sample Instrumental Variable Analysis.

Authors:  Rachael A Hughes; Neil M Davies; George Davey Smith; Kate Tilling
Journal:  Epidemiology       Date:  2019-05       Impact factor: 4.822

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