Hidden biases in observational epidemiology: the case of unmeasured confounding-Reference-Cited by-同舟云学术

Hidden biases in observational epidemiology: the case of unmeasured confounding

Published:2017-11-17 Issue:6 Volume:125 Page:644-646
ISSN:1470-0328
Container-title:BJOG: An International Journal of Obstetrics & Gynaecology
language:en
Short-container-title:BJOG: Int J Obstet Gy

Author:

Ananth CV¹²,Schisterman EF³

Affiliation:

1. Department of Obstetrics and Gynecology; College of Physicians and Surgeons; Columbia University; New York NY USA

2. Department of Epidemiology; Joseph L. Mailman School of Public Health; Columbia University; New York NY USA

3. Epidemiology Branch; Division of Intramural Population Health Research; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health; Bethesda MD USA

Publisher

Wiley

Subject

Obstetrics and Gynecology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/1471-0528.14960/fullpdf

Reference7 articles.

1. A definition of causal effect for epidemiological research;Hernan;J Epidemiol Community Health,2004

2. Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders;Vanderweele;Epidemiology,2011

3. Conditioning on intermediates in perinatal epidemiology;Vanderweele;Epidemiology,2012

4. Applying Quantitative Bias Analysis to Epidemiologic Data

5. Perinatal and maternal morbidity and mortality among term singletons following midcavity operative vaginal delivery versus caesarean delivery;Muraca;BJOG,2017

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