Ambarish Chattopadhyay | DeepAI

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Jose R. Zubizarreta
18 publications
Noah Greifer
6 publications
Eric R. Cohn
3 publications
Carl N. Morris
2 publications

∙ 05/23/2023

Notes on Causation, Comparison, and Regression

Comparison and contrast are the basic means to unveil causation and lear...

0 Ambarish Chattopadhyay, et al. ∙

∙ 03/15/2023

lmw: Linear Model Weights for Causal Inference

The linear regression model is widely used in the biomedical and social ...

0 Ambarish Chattopadhyay, et al. ∙

∙ 05/19/2022

Balanced and robust randomized treatment assignments: the Finite Selection Model

The Finite Selection Model (FSM) was proposed and developed by Carl Morr...

0 Ambarish Chattopadhyay, et al. ∙

∙ 03/16/2022

One-step weighting to generalize and transport treatment effect estimates to a target population

Weighting methods are often used to generalize and transport estimates o...

0 Ambarish Chattopadhyay, et al. ∙

∙ 05/06/2021

Randomized and Balanced Allocation of Units into Treatment Groups Using the Finite Selection Model for R

The original Finite Selection Model (FSM) was developed in the 1970s to ...

0 Ambarish Chattopadhyay, et al. ∙

∙ 04/14/2021

On the implied weights of linear regression for causal inference

In this paper, we derive and analyze the implied weights of linear regre...

0 Ambarish Chattopadhyay, et al. ∙

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