A Crash Course in Good and Bad Controls

Graphical criteria for efficient total effect estimation via adjustment in causal linear models

(2022) Leonard Henckel et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

An Introduction to Causal Diagrams for Anesthesiology Research

(2020) Amy L. Gaskell et al.   ANESTHESIOLOGY

Making sense of sensitivity: extending omitted variable bias

(2019) Carlos Cinelli et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Conceptual framework for investigating causal effects from observational data in livestock1

(2018) Nora M Bello et al.   JOURNAL OF ANIMAL SCIENCE

Identifying Causal Effects with the R Package causaleffect

(2017) Santtu Tikka et al.   Journal of Statistical Software

Causal inference and the data-fusion problem

(2016) Elias Bareinboim et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A flexible, interpretable framework for assessing sensitivity to unmeasured confounding

(2016) Vincent Dorie et al.   STATISTICS IN MEDICINE

Causal Inference Using Graphical Models with theRPackagepcalg

(2015) Markus Kalisch et al.   Journal of Statistical Software

The “Obesity Paradox” Explained

(2013) Hailey R. Banack et al.   EPIDEMIOLOGY

Invited Commentary: Understanding Bias Amplification

(2011) J. Pearl   AMERICAN JOURNAL OF EPIDEMIOLOGY

Should observational studies be designed to allow lack of balance in covariate distributions across treatment groups?

(2009) Donald B. Rubin   STATISTICS IN MEDICINE

Propensity scores

(2009) Ian Shrier   STATISTICS IN MEDICINE

Propensity scores and M-structures

(2009) Arvid Sjölander   STATISTICS IN MEDICINE