2 citations · 8 across the 9 of their papers we have counts for
9 papers
An Anatomy of Event Studies: Hypothetical Experiments, Exact Decomposition, and Weighting Diagnostics
Zhu Shen, Ambarish Chattopadhyay, Yuzhou Lin +1
In recent decades, event studies have become widely used in health and social research to estimate the dynamic effects of staggered interventions. In this paper, we develop a frame…
Neymanian inference in randomized experiments
Ambarish Chattopadhyay, Guido W. Imbens
In his seminal 1923 work, Neyman studied the variance estimation problem for the difference-in-means estimator of the average treatment effect in completely randomized experiments.…
Design-based inference for generalized network experiments with stochastic interventions
Ambarish Chattopadhyay, Kosuke Imai, Jose R. Zubizarreta
A growing number of researchers are conducting randomized experiments to analyze causal relationships in network settings where units influence one another. A dominant methodology…
Notes on Causation, Comparison, and Regression
Ambarish Chattopadhyay, Jose R. Zubizarreta
Comparison and contrast are the basic means to unveil causation and learn which treatments work. To build good comparison groups, randomized experimentation is key, yet often infea…
lmw: Linear Model Weights for Causal Inference
Ambarish Chattopadhyay, Noah Greifer, Jose R. Zubizarreta
The linear regression model is widely used in the biomedical and social sciences as well as in policy and business research to adjust for covariates and estimate the average effect…
Balanced and Robust Randomized Treatment Assignments: The Finite Selection Model for the Health Insurance Experiment and Beyond
Ambarish Chattopadhyay, Carl N. Morris, Jose R. Zubizarreta
The Finite Selection Model (FSM) was developed by Carl Morris in the 1970s for the design of the RAND Health Insurance Experiment (HIE) (Morris 1979, Newhouse et al. 1993), one of…
One-Step weighting to generalize and transport treatment effect estimates to a target population
Ambarish Chattopadhyay, Eric R. Cohn, Jose R. Zubizarreta
The problem of generalization and transportation of treatment effect estimates from a study sample to a target population is central to empirical research and statistical methodolo…
Randomized and Balanced Allocation of Units into Treatment Groups Using the Finite Selection Model for R
Ambarish Chattopadhyay, Carl N. Morris, Jose R. Zubizarreta
The original Finite Selection Model (FSM) was developed in the 1970s to enhance the design of the RAND Health Insurance Experiment (HIE; Newhouse et al. 1993). At the time of its d…
On the implied weights of linear regression for causal inference
Ambarish Chattopadhyay, Jose R. Zubizarreta
A basic principle in the design of observational studies is to approximate the randomized experiment that would have been conducted under controlled circumstances. Now, linear regr…