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Matched Sampling for Causal Effects

Details

  • 108 tables
  • Page extent: 502 pages
  • Size: 228 x 152 mm
  • Weight: 0.676 kg

Paperback

 (ISBN-13: 9780521674362 | ISBN-10: 0521674360)




Contents

Contributor Acknowledgments page ix
    My Introduction to Matched Sampling 1
PART I.  THE EARLY YEARS AND THE INFLUENCE OF WILLIAM G. COCHRAN 5
1.   William G. Cochran’s Contributions to the Design, Analysis, and Evaluation of Observational Studies 7
    Donald B. Rubin (1984)  
2.   Controlling Bias in Observational Studies: A Review 30
    William G. Cochran and Donald B. Rubin (1973)  
PART II.  UNIVARIATE MATCHING METHODS AND THE DANGERS OF REGRESSION ADJUSTMENT 59
3.   Matching to Remove Bias in Observational Studies 62
    Donald B. Rubin (1973)  
4.   The Use of Matched Sampling and Regression Adjustment to Remove Bias in Observational Studies 81
    Donald B. Rubin (1973)  
5.   Assignment to Treatment Group on the Basis of a Covariate 99
    Donald B. Rubin (1977)  
PART III.  BASIC THEORY OF MULTIVARIATE MATCHING 115
6.   Multivariate Matching Methods That Are Equal Percent Bias Reducing, I: Some Examples 117
    Donald B. Rubin (1976)  
7.   Multivariate Matching Methods That Are Equal Percent Bias Reducing, Ⅱ: Maximums on Bias Reduction for Fixed Sample Sizes 129
    Donald B. Rubin (1976)  
8.   Using Multivariate Matched Sampling and Regression Adjustment to Control Bias in Observational Studies 142
    Donald B. Rubin (1979)  
9.   Bias Reduction Using Mahalanobis-Metric Matching 160
    Donald B. Rubin (1980)  
PART IV.  FUNDAMENTALS OF PROPENSITY SCORE MATCHING 167
10.   The Central Role of the Propensity Score in Observational Studies for Causal Effects 170
    Paul R. Rosenbaum and Donald B. Rubin (1983)  
11.   Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome 185
    Paul R. Rosenbaum and Donald B. Rubin (1983)  
12.   Reducing Bias in Observational Studies Using Subclassification on the Propensity Score 193
    Paul R. Rosenbaum and Donald B. Rubin (1984)  
13.   Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score 207
    Paul R. Rosenbaum and Donald B. Rubin (1985)  
14.   The Bias Due to Incomplete Matching 217
    Paul R. Rosenbaum and Donald B. Rubin (1985)  
PART V.  AFFINELY INVARIANT MATCHING METHODS WITH ELLIPSOIDALLY SYMMETRIC DISTRIBUTIONS, THEORY AND METHODOLOGY 233
15.   Affinely Invariant Matching Methods with Ellipsoidal Distributions 235
    Donald B. Rubin and Neal Thomas (1992)  
16.   Characterizing the Effect of Matching Using Linear Propensity Score Methods with Normal Distributions 249
    Donald B. Rubin and Neal Thomas (1992)  
17.   Matching Using Estimated Propensity Scores: Relating Theory to Practice 263
    Donald B. Rubin and Neal Thomas (1996)  
18.   Combining Propensity Score Matching with Additional Adjustments for Prognostic Covariates 282
    Donald B. Rubin and Neal Thomas (2000)  
PART VI.  SOME APPLIED CONTRIBUTIONS 305
19.   Causal Inference in Retrospective Studies 308
    Paul W. Holland and Donald B. Rubin (1988)  
20.   The Design of the New York School Choice Scholarships Program Evaluation 328
    Jennifer L. Hill, Donald B. Rubin, and Neal Thomas (1999)  
21.   Estimating and Using Propensity Scores with Partially Missing Data 347
    Ralph B. D’Agostino, Jr., and Donald B. Rubin (2000)  
22.   Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation 365
    Donald B. Rubin (2001)  
PART VII.  SOME FOCUSED APPLICATIONS 383
23.   Criminality in XYY and XXY Men 385
    Herman A. Witkin, Sarnoff A. Mednick, Fini Schulsinger, Eskild Bakkestrøm, Karl O. Christiansen, Donald R. Goodenough, Kurt Hirschhorn, Claes Lundsteen, David R. Owen, John Philip, Donald B. Rubin, and Martha Stocking (1976)  
24.   Practical Implications of Modes of Statistical Inference for Causal Effects and the Critical Role of the Assignment Mechanism 402
    Donald B. Rubin (1991)  
25.   In Utero Exposure to Phenobarbital and Intelligence Deficits in Adult Men 426
    June Machover Reinisch, Stephanie A. Sanders, Erik Lykke Mortensen, and Donald B. Rubin (1995)  
26.   Estimating Causal Effects from Large Data Sets Using Propensity Scores 443
    Donald B. Rubin (1997)  
27.   On Estimating the Causal Effects of DNR Orders 455
    Martin W. McIntosh and Donald B. Rubin (1999)  
    Conclusion: Advice to the Investigator 460
References 463
Author Index 483
Subject Index 487

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