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Causal Inference (The MIT Press Essential Knowledge series)

Description:

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? Does winning the lottery make you more or less likely to go bankrupt? How do you identify genes that cause disease? Do unions raise wages? Do some antibiotics have lethal side effects? Does the Earned Income Tax Credit help people enter the workforce?

Causal Inference provides a brief and nontechnical introduction to randomized experiments, propensity scores, natural experiments, instrumental variables, sensitivity analysis, and quasi-experimental devices. Ideas are illustrated with examples from medicine, epidemiology, economics and business, the social sciences, and public policy.


Editorial Reviews

About the Author

Paul R. Rosenbaum is the Robert G. Putzel Professor Emeritus of Statistics and Data Science at the Wharton School of the University of Pennsylvania. He is the author of Observation and Experiment: An Introduction to Causal Inference, Design of Observational Studies, Observational Studies, and Replication and Evidence Factors in Observational Studies.

Reviews:

5.0 out of 5 stars Dense, but worth it

t. · July 13, 2025

one of the coolest books ive ever read so far

5.0 out of 5 stars Good book

E. · December 4, 2023

Nice book for the lovers of casual inference

5.0 out of 5 stars Excellent book

S. · May 10, 2023

Very well written and concise.

4.0 out of 5 stars Good Content Quality in Tidy Scope

G.M. · November 18, 2024

This is a nicely done overview of the subject matter. Greater details are not necessary for many of us, and might even complicate the topics. A handy keeper reference book for what I do in the quality discipline.

5.0 out of 5 stars Well-written good intro book for any audience

G. · May 1, 2023

It is a well-written a good introduction book for experimentation, propensity matching, causal inference for any audience. The only complain I have is book is too verbose in terms of explanations. Many of the pages can be reduced to a single mathematical formula that anyone can understand.

5.0 out of 5 stars Excellent introduction to causal inference.

A.M. · April 17, 2023

The book is geared towards a non-technical audience as a primer towards causal inference in regards to study design (randomized, quasi, and observational). The book details the concepts around causal inference and supports this with examples through the research literature. The book is well-written with lucid explanations. I especially enjoyed reading through the lines and seeing clearly that the author is influenced by philosophy. This scientific and philosophy thinking was a joy to read.

Great introduction to causality. How to spot when youtubers are making stuff up

M.J.H. · May 21, 2025

Excellent summary of modern techniques for identifying cause

Recomendo

A. · July 25, 2025

Boa introdução para inferência causal.

Como saber se as unidades são comparáveis?

C.K. · August 21, 2024

Perguntas que esse livro ajuda a responder:- O que é causalidade e como analisar? (Em linhas gerais)- Como saber se o que você está analisando é de fato comparável? Exemplo:O estado B é de fato comparável com o estado A?A escola A é comparável com a escola B?A pessoa X é comparável com a pessoa Y?É uma introdução a causalidade somada a introdução ao conceito de propensity Match score (score de propensão).É um livro simples quando comparado aos outros livros sobre o tema, mas muito útil pra se ter, pois fala sobre essa ciência de causalidade de maneira acessível e serve como referência caso precise responder alguma questão como as listadas lá em cima nesse comentário aqui.Pessoalmente eu acho que ele poderia falar um pouco mais sobre o cálculo de escore de propensão em si e até mesmo ter um link pra o repositório de código no GitHub com exemplos reprodutiveis, mas o livro pelo que vi é meio antigo e o foco é em realmente introduzir

O conteúdo é muito bom

M.C. · April 7, 2024

Mas a fonte é incrivelmente pequena. tornando a leitura difícil

Somewhat slow

M.P.B.(. · March 22, 2024

Good book but slow in developing the arguments.

Causal Inference (The MIT Press Essential Knowledge series)

Product ID: U0262545195
Condition: New

4.5

AED7400

Price includes VAT & Import Duties
Type: Paperback
Availability: In Stock

Quantity:

|

Order today to get by 7-14 business days

Delivery fee of AED 20. Free for orders above AED 200.

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Imported From: United States

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Unless otherwise stated, all prices displayed on the product page include applicable taxes and import duties.

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Causal Inference (The MIT Press Essential Knowledge series)

Product ID: U0262545195
Condition: New

4.5

Causal Inference (The MIT Press Essential Knowledge series)-0
Type: Paperback

AED7400

Price includes VAT & Import Duties
Availability: In Stock

Quantity:

|

Order today to get by 7-14 business days

Delivery fee of AED 20. Free for orders above AED 200.

Returns & Warranty policies

Imported From: United States

At BOLO, we work hard to ensure the products you receive are new, genuine, and sourced from reputable suppliers.

BOLO is not an authorized or official retailer for most brands, nor are we affiliated with manufacturers unless specifically stated on a product page. Instead, we source verified sellers, authorized distributors or directly from the manufacturer.

Each product undergoes thorough inspection and verification at our consolidation and fulfilment centers to ensure it meets our strict authenticity and quality standards before being shipped and delivered to you.

If you ever have concerns regarding the authenticity of a product purchased from us, please contact Bolo Support. We will review your inquiry promptly and, if necessary, provide documentation verifying authenticity or offer a suitable resolution.

Your trust is our top priority, and we are committed to maintaining transparency and integrity in every transaction.

All product information, images, descriptions, and reviews originate from the manufacturer or from trusted sellers overseas. BOLO is not affiliated with, endorsed by, or an authorized retailer for most brands listed on our website unless stated otherwise.

While we strive to display accurate information, variations in packaging, labeling, instructions, or formulation may occasionally occur due to regional differences or supplier updates. For detailed or manufacturer-specific information, please contact the brand directly or reach out to BOLO Support for assistance.

Unless otherwise stated, all prices displayed on the product page include applicable taxes and import duties.

BOLO operates in accordance with the laws and regulations of United Arab Emirates. Any items found to be restricted or prohibited for sale within the UAE will be cancelled prior to shipment. We take proactive measures to ensure that only products permitted for sale in United Arab Emirates are listed on our website.

All items are shipped by air, and any products classified as “Dangerous Goods (DG)” under IATA regulations will be removed from the order and cancelled.

All orders are processed manually, and we make every effort to process them promptly once confirmed. Products cancelled due to the above reasons will be permanently removed from listings across the website.

Description:

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? Does winning the lottery make you more or less likely to go bankrupt? How do you identify genes that cause disease? Do unions raise wages? Do some antibiotics have lethal side effects? Does the Earned Income Tax Credit help people enter the workforce?

Causal Inference provides a brief and nontechnical introduction to randomized experiments, propensity scores, natural experiments, instrumental variables, sensitivity analysis, and quasi-experimental devices. Ideas are illustrated with examples from medicine, epidemiology, economics and business, the social sciences, and public policy.


Editorial Reviews

About the Author

Paul R. Rosenbaum is the Robert G. Putzel Professor Emeritus of Statistics and Data Science at the Wharton School of the University of Pennsylvania. He is the author of Observation and Experiment: An Introduction to Causal Inference, Design of Observational Studies, Observational Studies, and Replication and Evidence Factors in Observational Studies.

Reviews:

5.0 out of 5 stars Dense, but worth it

t. · July 13, 2025

one of the coolest books ive ever read so far

5.0 out of 5 stars Good book

E. · December 4, 2023

Nice book for the lovers of casual inference

5.0 out of 5 stars Excellent book

S. · May 10, 2023

Very well written and concise.

4.0 out of 5 stars Good Content Quality in Tidy Scope

G.M. · November 18, 2024

This is a nicely done overview of the subject matter. Greater details are not necessary for many of us, and might even complicate the topics. A handy keeper reference book for what I do in the quality discipline.

5.0 out of 5 stars Well-written good intro book for any audience

G. · May 1, 2023

It is a well-written a good introduction book for experimentation, propensity matching, causal inference for any audience. The only complain I have is book is too verbose in terms of explanations. Many of the pages can be reduced to a single mathematical formula that anyone can understand.

5.0 out of 5 stars Excellent introduction to causal inference.

A.M. · April 17, 2023

The book is geared towards a non-technical audience as a primer towards causal inference in regards to study design (randomized, quasi, and observational). The book details the concepts around causal inference and supports this with examples through the research literature. The book is well-written with lucid explanations. I especially enjoyed reading through the lines and seeing clearly that the author is influenced by philosophy. This scientific and philosophy thinking was a joy to read.

Great introduction to causality. How to spot when youtubers are making stuff up

M.J.H. · May 21, 2025

Excellent summary of modern techniques for identifying cause

Recomendo

A. · July 25, 2025

Boa introdução para inferência causal.

Como saber se as unidades são comparáveis?

C.K. · August 21, 2024

Perguntas que esse livro ajuda a responder:- O que é causalidade e como analisar? (Em linhas gerais)- Como saber se o que você está analisando é de fato comparável? Exemplo:O estado B é de fato comparável com o estado A?A escola A é comparável com a escola B?A pessoa X é comparável com a pessoa Y?É uma introdução a causalidade somada a introdução ao conceito de propensity Match score (score de propensão).É um livro simples quando comparado aos outros livros sobre o tema, mas muito útil pra se ter, pois fala sobre essa ciência de causalidade de maneira acessível e serve como referência caso precise responder alguma questão como as listadas lá em cima nesse comentário aqui.Pessoalmente eu acho que ele poderia falar um pouco mais sobre o cálculo de escore de propensão em si e até mesmo ter um link pra o repositório de código no GitHub com exemplos reprodutiveis, mas o livro pelo que vi é meio antigo e o foco é em realmente introduzir

O conteúdo é muito bom

M.C. · April 7, 2024

Mas a fonte é incrivelmente pequena. tornando a leitura difícil

Somewhat slow

M.P.B.(. · March 22, 2024

Good book but slow in developing the arguments.

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More from this brand

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