Causal inference for statistics, social, and biomedical sciences : an introduction /
Imbens, Guido W.
Causal inference for statistics, social, and biomedical sciences : an introduction / Guido W. Imbens, Stanford University, Donald B. Rubin, Harvard University - New York : Cambridge University Press, 2015 - xix, 625 pages ; 26 cm
Includes bibliographical references and index
Part 1: Introduction -- Causality: The Basic Framework -- A Brief History of the Potential Outcomes Approach to Causal Inference -- A Classification of Assignment Mechanisms -- Part 2: Classical Randomized Experiments -- A Taxonomy of Classical Randomized Experiments -- Fisher's Exact P-Values for Completely Randomized Experiments -- Neyman's Repeated Sampling Approach to Completely Randomized Experiments -- Regression Methods for Completely Randomized Experiments -- Model-Based Inference for Completely Randomized Experiments -- Stratified Randomized Experiments -- Pairwise Randomized Experiments -- Case Study: An Experimental Evaluation of a Labor Market Program -- Part 3: Regular Assignment Mechanisms: Design -- Unconfounded Treatment Assignment -- Estimating the Propensity Score -- Assessing Overlap in Covariate Distributions -- Matching to Improve Balance in Covariate Distributions -- Trimming to Improve Balance in Covariate Distribution -- Part 4: Regular Assignment Mechanisms: Analysis -- Subclassification on the Propensity Score -- Matching Estimators -- A General Method for Estimating Sampling Variances for Standard Estimators for Average Causal Effects -- Inference for General Causal Estimands -- Part 5: Regular Assignment Mechanisms: Supplementary Analyses -- Assessing Unconfoundedness -- Sensitivity Analysis and Bounds -- Part 6: Regular Assignment Mechanisms with Noncompliance: Analysis -- Instrumental Variables Analysis of Randomized Experiments with One-Sided Noncompliance -- Instrumental Variables Analysis of Randomized Experiments with Two-Sided Noncompliance -- Model-Based Analysis in Instrumental Variable Settings: Randomized Experiments with Two-Sided Noncompliance -- Part 7: Conclusion -- Conclusions and Extensions
9780521885881
2014020988
SOCIAL SCIENCES--RESEARCH
CAUSATION
INFERENCE
H 62 / I42C 2015
Causal inference for statistics, social, and biomedical sciences : an introduction / Guido W. Imbens, Stanford University, Donald B. Rubin, Harvard University - New York : Cambridge University Press, 2015 - xix, 625 pages ; 26 cm
Includes bibliographical references and index
Part 1: Introduction -- Causality: The Basic Framework -- A Brief History of the Potential Outcomes Approach to Causal Inference -- A Classification of Assignment Mechanisms -- Part 2: Classical Randomized Experiments -- A Taxonomy of Classical Randomized Experiments -- Fisher's Exact P-Values for Completely Randomized Experiments -- Neyman's Repeated Sampling Approach to Completely Randomized Experiments -- Regression Methods for Completely Randomized Experiments -- Model-Based Inference for Completely Randomized Experiments -- Stratified Randomized Experiments -- Pairwise Randomized Experiments -- Case Study: An Experimental Evaluation of a Labor Market Program -- Part 3: Regular Assignment Mechanisms: Design -- Unconfounded Treatment Assignment -- Estimating the Propensity Score -- Assessing Overlap in Covariate Distributions -- Matching to Improve Balance in Covariate Distributions -- Trimming to Improve Balance in Covariate Distribution -- Part 4: Regular Assignment Mechanisms: Analysis -- Subclassification on the Propensity Score -- Matching Estimators -- A General Method for Estimating Sampling Variances for Standard Estimators for Average Causal Effects -- Inference for General Causal Estimands -- Part 5: Regular Assignment Mechanisms: Supplementary Analyses -- Assessing Unconfoundedness -- Sensitivity Analysis and Bounds -- Part 6: Regular Assignment Mechanisms with Noncompliance: Analysis -- Instrumental Variables Analysis of Randomized Experiments with One-Sided Noncompliance -- Instrumental Variables Analysis of Randomized Experiments with Two-Sided Noncompliance -- Model-Based Analysis in Instrumental Variable Settings: Randomized Experiments with Two-Sided Noncompliance -- Part 7: Conclusion -- Conclusions and Extensions
9780521885881
2014020988
SOCIAL SCIENCES--RESEARCH
CAUSATION
INFERENCE
H 62 / I42C 2015