Description: BRAND NEW FIRST EDITION hardcover, clean NEW text, solid binding, NO remainders NOT ex-library, smoke-free; slight gentle shelfwear / storage wear; WE SHIP FAST. Carefully packed and quickly sent. Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including, matching, propensity score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.4 02 231
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Item Specifics
All returns accepted: ReturnsNotAccepted
Number of Pages: 644 Pages
Language: English
Publication Name: Causal Inference for Statistics, Social, and Biomedical Sciences : an Introduction
Publisher: Cambridge University Press
Publication Year: 2015
Subject: Probability & Statistics / General, General, Research, Logic
Item Height: 1.3 in
Item Weight: 45.2 Oz
Type: Textbook
Item Length: 10.3 in
Author: Donald B. Rubin, Guido W. Imbens
Subject Area: Mathematics, Philosophy, Social Science
Item Width: 7.3 in
Format: Hardcover
