4.6 Article

To Adjust or Not to Adjust? When a Confounder Is Only Measured After Exposure

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Public, Environmental & Occupational Health

Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs

Karl D. Ferguson et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2020)

Article Statistics & Probability

Robust inference on population indirect causal effects: the generalized front door criterion

Isabel R. Fulcher et al.

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2020)

Article Public, Environmental & Occupational Health

Principles of confounder selection

Tyler J. VanderWeele

EUROPEAN JOURNAL OF EPIDEMIOLOGY (2019)

Article Public, Environmental & Occupational Health

Accounting for missing data in statistical analyses: multiple imputation is not always the answer

Rachael A. Hughes et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2019)

Article Public, Environmental & Occupational Health

Estimation of Natural Indirect Effects Robust to Unmeasured Confounding and Mediator Measurement Error

Isabel R. Fulcher et al.

EPIDEMIOLOGY (2019)

Article Public, Environmental & Occupational Health

Educational Note: Paradoxical collider effect in the analysis of non-communicable disease epidemiological data: a reproducible illustration and web application

Miguel Angel Luque-Fernandez et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2019)

Article Public, Environmental & Occupational Health

Collider scope: when selection bias can substantially influence observed associations

Marcus R. Munafo et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2018)

Review Mathematical & Computational Biology

Variable selection - A review and recommendations for the practicing statistician

Georg Heinze et al.

BIOMETRICAL JOURNAL (2018)

Article Public, Environmental & Occupational Health

Vitamin K antagonist use and renal function in pre-dialysis patients

Pauline W. M. Voskamp et al.

CLINICAL EPIDEMIOLOGY (2018)

Article Urology & Nephrology

Use of Causal Diagrams to Inform the Design and Interpretation of Observational Studies: An Example from the Study of Heart and Renal Protection (SHARP)

Natalie Staplin et al.

CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY (2017)

Article Mathematical & Computational Biology

A Theorem at the Core of Colliding Bias

Doron J. Shahar et al.

INTERNATIONAL JOURNAL OF BIOSTATISTICS (2017)

Article Public, Environmental & Occupational Health

Migraine and risk of stroke and acute coronary syndrome in two case-control studies in the Danish population

Merete Osler et al.

CLINICAL EPIDEMIOLOGY (2017)

Article Psychology, Multidisciplinary

When Is Higher Neuroticism Protective Against Death? Findings From UK Biobank

Catharine R. Gale et al.

PSYCHOLOGICAL SCIENCE (2017)

Article Medicine, General & Internal

Sensitivity Analysis in Observational Research: Introducing the E-Value

Tyler J. VanderWeele et al.

ANNALS OF INTERNAL MEDICINE (2017)

Article Obstetrics & Gynecology

Confounding, causality, and confusion: the role of intermediate variables in interpreting observational studies in obstetrics

Cande V. Ananth et al.

AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY (2017)

Article Public, Environmental & Occupational Health

Sensitivity analysis for the effects of multiple unmeasured confounders

Rolf H. H. Groenwold et al.

ANNALS OF EPIDEMIOLOGY (2016)

Article Mathematics, Interdisciplinary Applications

The Mechanics of Omitted Variable Bias: Bias Amplification and Cancellation of Offsetting Biases

Peter M. Steiner et al.

JOURNAL OF CAUSAL INFERENCE (2016)

Article Mathematics, Interdisciplinary Applications

To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias

Peng Ding et al.

JOURNAL OF CAUSAL INFERENCE (2015)

Editorial Material Public, Environmental & Occupational Health

Selection Bias as an Explanation for the Obesity Paradox Just Because It's Possible Doesn't Mean It's Plausible

M. Maria Glymour et al.

EPIDEMIOLOGY (2014)

Review Respiratory System

Introduction to causal diagrams for confounder selection

Elizabeth J. Williamson et al.

RESPIROLOGY (2014)

Article Statistics & Probability

ON THE DEFINITION OF A CONFOUNDER

Tyler J. Vanderweele et al.

ANNALS OF STATISTICS (2013)

Article Mathematical & Computational Biology

Sensitivity Analysis for Causal Inference under Unmeasured Confounding and Measurement Error Problems

Ivan Diaz et al.

INTERNATIONAL JOURNAL OF BIOSTATISTICS (2013)

Article Mathematics, Interdisciplinary Applications

Linear Models: A Useful Microscope for Causal Analysis

Judea Pearl

JOURNAL OF CAUSAL INFERENCE (2013)

Article Public, Environmental & Occupational Health

Conditioning on Intermediates in Perinatal Epidemiology

Tyler J. VanderWeele et al.

EPIDEMIOLOGY (2012)

Article Computer Science, Interdisciplinary Applications

lavaan: An R Package for Structural Equation Modeling

Yves Rosseel

JOURNAL OF STATISTICAL SOFTWARE (2012)

Article Biology

A New Criterion for Confounder Selection

Tyler J. VanderWeele et al.

BIOMETRICS (2011)

Article Public, Environmental & Occupational Health

Sensitivity analyses to estimate the potential impact of unmeasured confounding in causal research

Rolf H. H. Groenwold et al.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2010)

Article Public, Environmental & Occupational Health

Overadjustment Bias and Unnecessary Adjustment in Epidemiologic Studies

Enrique F. Schisterman et al.

EPIDEMIOLOGY (2009)

Article Public, Environmental & Occupational Health

Bias formulas for external adjustment and sensitivity analysis of unmeasured confounders

Onyebuchi A. Arah et al.

ANNALS OF EPIDEMIOLOGY (2008)

Article Health Care Sciences & Services

Reducing bias through directed acyclic graphs

Ian Shrier et al.

BMC MEDICAL RESEARCH METHODOLOGY (2008)

Article Public, Environmental & Occupational Health

The impact of residual and unmeasured confounding in epidemiologic studies: A simulation study

Zoe Fewell et al.

AMERICAN JOURNAL OF EPIDEMIOLOGY (2007)

Article Mathematical & Computational Biology

Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures

BA Brumback et al.

STATISTICS IN MEDICINE (2004)