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Demystifying Causal Inference

2023
This book provides an accessible introduction to causal inference and data analysis with R, specifically for a public policy audience. It aims to demystify these topics by presenting them through practical policy examples from a range of disciplines. It provides a hands-on approach to working with data in R using the popular tidyverse package.
Dayal, Vikram, Murugesan, Anand
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Causal Inference

Abstract This chapter is a refresher on the standard tools and techniques for performing causal inference that will be used throughout the book. We begin by introducing the potential outcome model and the parameters of interest, and then present inference on the latter in the context of randomized controlled trials (RCTs), which are the ...
Christophe Gaillac, Jérémy L'Hour
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Causal Inference

2023
A nontechnical guide to the basic ideas of modern causal inference, with illustrations from health, the economy, and public policy. Which of two antiviral drugs does the most to save people infected with Ebola virus? Does a daily glass of wine prolong or shorten life?
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Inferring causality

Journal of PeriAnesthesia Nursing, 1996
The goal of research is to discover new knowledge to improve patient care. Research is essential because of its ability to establish causal relationships. This article discusses the minimum requirements a research report must meet to establish a causal relationship.
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Causal Estimation and Causal Inference

2020
This entry provides an introduction to causal inference. Causal inference refers to the estimation of the effect of a treatment, policy, or intervention on an outcome of interest. Causal inference is, therefore, at the centre of science and social sciences. This entry emphasises Rubin’s potential outcomes framework.
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Causal Inference

Journal of Statistical Computation and Simulation, 2022
Fabian Dablander, Riet van Bork
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Causal inferences

2002
[Chemnitz] 24th Tagung experimentell arbeitender Psychologen, 1 maart ...
Noordman, L.G.M., Vonk, W.
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