---
product_id: 13719318
title: "Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction"
price: "$644850"
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---

# Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction

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## Description

desertcart.com: Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction: 9780521885881: Imbens, Guido W., Rubin, Donald B.: Books

Review: A good reference text/introduction to causal inference using Propensity Score analysis - Some people are of the opinion that statistics should replace calculus in high school/college curricula because of the importance of analytics in the modern business world. I think a similar argument could be made about replacing some of the more esoteric parts of graduate statistics/econometrics with causal inference theory. If that opinion is correct, this would be an excellent reference text. Causal inference theory is important because the regression techniques now taught to young social scientists as methods of determining cause and effect assume endogeneity when the data often don't support such an assumption. They also impose a linear model on the data that can be similarly inappropriate. The non-parametric techniques discussed by Rubin and Imbens, while having their own assumptions, are applicable to a wider range of problems. Rubin and Imbens summarize the voluminous literature on propensity score and related causal inference techniques in a manner that is accessible to someone with a solid background in statistics (both frequentist and Bayesian). I read the book cover to cover and, despite already knowing something about Propensity Score techniques, learned a great deal. They begin with randomized experiments then explain how the mathematical models developed for such methods are also applicable to observational studies. They then discuss various methods of using the Propensity Score along with tests of the plausibility of such models and bias limits when some of the assumptions in these models are relaxed. One complaint I have is that the different types of exact matching are barely discussed. Considering the growing importance of techniques like Coarsened Exact Matching, this seems like a significant oversight. In addition, the book contains no exercises making it difficult to use as a textbook without some supplementary material. All in all, though, this work is a must have for those engaged in Causal Inference either academically or in the business world. Even those not making active use of these techniques might find applications to their empirical work once they understand how to properly use Propensity Score analysis.
Review: Thick - Well written book. Already start reading it for my research

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #413,270 in Books ( See Top 100 in Books ) #196 in Sociology Research & Measurement #219 in Social Sciences Research #329 in Probability & Statistics (Books) |
| Customer Reviews | 4.7 4.7 out of 5 stars (101) |
| Dimensions  | 7.5 x 1.25 x 10.5 inches |
| Edition  | 1st |
| ISBN-10  | 0521885884 |
| ISBN-13  | 978-0521885881 |
| Item Weight  | 2.8 pounds |
| Language  | English |
| Print length  | 644 pages |
| Publication date  | April 6, 2015 |
| Publisher  | Cambridge University Press |

## Images

![Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction - Image 1](https://m.media-amazon.com/images/I/71DF-T7N33L.jpg)
![Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction - Image 2](https://m.media-amazon.com/images/I/81fsmMp0mCL.jpg)
![Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction - Image 3](https://m.media-amazon.com/images/I/31VMpt4gXiL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ A good reference text/introduction to causal inference using Propensity Score analysis
*by A***S on January 22, 2017*

Some people are of the opinion that statistics should replace calculus in high school/college curricula because of the importance of analytics in the modern business world. I think a similar argument could be made about replacing some of the more esoteric parts of graduate statistics/econometrics with causal inference theory. If that opinion is correct, this would be an excellent reference text. Causal inference theory is important because the regression techniques now taught to young social scientists as methods of determining cause and effect assume endogeneity when the data often don't support such an assumption. They also impose a linear model on the data that can be similarly inappropriate. The non-parametric techniques discussed by Rubin and Imbens, while having their own assumptions, are applicable to a wider range of problems. Rubin and Imbens summarize the voluminous literature on propensity score and related causal inference techniques in a manner that is accessible to someone with a solid background in statistics (both frequentist and Bayesian). I read the book cover to cover and, despite already knowing something about Propensity Score techniques, learned a great deal. They begin with randomized experiments then explain how the mathematical models developed for such methods are also applicable to observational studies. They then discuss various methods of using the Propensity Score along with tests of the plausibility of such models and bias limits when some of the assumptions in these models are relaxed. One complaint I have is that the different types of exact matching are barely discussed. Considering the growing importance of techniques like Coarsened Exact Matching, this seems like a significant oversight. In addition, the book contains no exercises making it difficult to use as a textbook without some supplementary material. All in all, though, this work is a must have for those engaged in Causal Inference either academically or in the business world. Even those not making active use of these techniques might find applications to their empirical work once they understand how to properly use Propensity Score analysis.

### ⭐⭐⭐⭐⭐ Thick
*by M***S on June 7, 2025*

Well written book. Already start reading it for my research

### ⭐⭐⭐⭐⭐ Great book, great condition, great service and delivery
*by Y***N on December 13, 2019*

Excellent book exactly directed toward checking the effect of drugs, chemicals and other factors on the population.

## Frequently Bought Together

- Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
- Counterfactuals and Causal Inference: Methods and Principles for Social Research (Analytical Methods for Social Research)

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*Product available on Desertcart Colombia*
*Store origin: CO*
*Last updated: 2026-03-07*