What Is Your Estimand? Defining the Target Quantity Connects Statistical Evidence to Theory

Models as Approximations I: Consequences Illustrated with Linear Regression

(2020) Andreas Buja et al.   STATISTICAL SCIENCE

Measuring the predictability of life outcomes with a scientific mass collaboration

(2020) Matthew J. Salganik et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Assumption Lean Regression

(2019) Richard Berk et al.   AMERICAN STATISTICIAN

The C-Word: Scientific Euphemisms Do Not Improve Causal Inference From Observational Data

(2018) Miguel A. Hernán   AMERICAN JOURNAL OF PUBLIC HEALTH

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

(2018) Stefan Wager et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Understanding and misunderstanding randomized controlled trials: A commentary on Deaton and Cartwright

(2018) Guido Imbens   SOCIAL SCIENCE & MEDICINE

Understanding and misunderstanding randomized controlled trials

(2018) Angus Deaton et al.   SOCIAL SCIENCE & MEDICINE

Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses

(2016) Miguel A. Hernán et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Recursive partitioning for heterogeneous causal effects: Table 1.

(2016) Susan Athey et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients

(2013) D. Westreich et al.   AMERICAN JOURNAL OF EPIDEMIOLOGY

Population heterogeneity and causal inference

(2013) Y. Xie   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Comparing IV with structural models: What simple IV can and cannot identify

(2009) James J. Heckman et al.   JOURNAL OF ECONOMETRICS