2 Statistical Inference for Causal Effects, With Emphasis on Applications in Epidemiology and Medical Statistics

[1]  Donald B. Rubin,et al.  Public Schools Versus Private Schools: Causal Inference With Partial Compliance , 2009 .

[2]  D. Rubin,et al.  Outcome-free Design of Observational Studies: Peer Influence on Smoking , 2008 .

[3]  D. Rubin.  The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials , 2007, Statistics in medicine.

[4]  Donald B. Rubin,et al.  Affinely invariant matching methods with discriminant mixtures of proportional ellipsoidally symmetric distributions , 2006, math/0611263.

[5]  Keyvan Karkouti,et al.  A propensity score case‐control comparison of aprotinin and tranexamic acid in high‐transfusion‐risk cardiac surgery , 2006, Transfusion.

[6]  D. Rubin.  24 Statistical Inference for Causal Effects, with Emphasis on Applications in Psychometrics and Education , 2006 .

[7]  D. Rubin.  Causal Inference Using Potential Outcomes , 2005 .

[8]  R. Fisher.  Statistical methods for research workers , 1927, Protoplasma.

[9]  D. Rubin.  Direct and Indirect Causal Effects via Potential Outcomes * , 2004 .

[10]  Donald B. Rubin,et al.  Assumptions when Analyzing Randomized Experiments with Noncompliance and Missing Outcomes , 2002, Health Services and Outcomes Research Methodology.

[11]  D. Rubin.  Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation , 2001, Health Services and Outcomes Research Methodology.

[12]  Donald B. Rubin,et al.  Estimation of Causal Effects via Principal Stratification When Some Outcomes are Truncated by “Death” , 2003 .

[13]  Charles F. Manski,et al.  Confidence Intervals for Partially Identified Parameters , 2003 .

[14]  A. Whittemore,et al.  Observational studies and randomized trials of hormone replacement therapy: what can we learn from them? , 2003, Epidemiology.

[15]  S. Piantadosi.  Larger lessons from the Women's Health Initiative. , 2003, Epidemiology.

[16]  Xiao-Hua Zhou,et al.  Clustered encouragement designs with individual noncompliance: bayesian inference with randomization, and application to advance directive forms. , 2002, Biostatistics.

[17]  D. Rubin,et al.  Principal Stratification in Causal Inference , 2002, Biometrics.

[18]  D. Rubin,et al.  School Choice in NY City: A Bayesian Analysis of an Imperfect Randomized Experiment , 2001 .

[19]  Jun S. Liu,et al.  Monte Carlo strategies in scientific computing , 2001 .

[20]  W. Shadish,et al.  Experimental and Quasi-Experimental Designs for Generalized Causal Inference , 2001 .

[21]  S. L. Mann,et al.  Hutchinson Smoking Prevention Project: long-term randomized trial in school-based tobacco use prevention--results on smoking. , 2000, Journal of the National Cancer Institute.

[22]  D. Rubin,et al.  Estimating and Using Propensity Scores with Partially Missing Data , 2000 .

[23]  D. Rubin.  Comment on "Causal inference without counterfactuals," by Dawid AP , 2000 .

[24]  A. Dawid,et al.  Causal Inference without Counterfactuals , 2000 .

[25]  D. Rubin,et al.  Assessing the effect of an influenza vaccine in an encouragement design. , 2000, Biostatistics.

[26]  P. Rosenbaum,et al.  Substantial Gains in Bias Reduction from Matching with a Variable Number of Controls , 2000, Biometrics.

[27]  J. Horowitz,et al.  Nonparametric Analysis of Randomized Experiments with Missing Covariate and Outcome Data , 2000 .

[28]  J. Pearl.  Causality: Models, Reasoning and Inference , 2000 .

[29]  D. Rubin,et al.  Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subsequent missing outcomes , 1999 .

[30]  J. Pearl,et al.  Confounding and Collapsibility in Causal Inference , 1999 .

[31]  Stuart G. Baker,et al.  Analysis of Survival Data from a Randomized Trial with All-or-None Compliance: Estimating the Cost-Effectiveness of a Cancer Screening Program , 1998 .

[32]  Daniel S. Nagin,et al.  3. Bounding Disagreements about Treatment Effects: A Case Study of Sentencing and Recidivism , 1998 .

[33]  R. Little,et al.  Statistical Techniques for Analyzing Data from Prevention Trials: Treatment of No-Shows Using Rubin's Causal Model , 1998 .

[34]  Donald Rubin,et al.  Estimating Causal Effects from Large Data Sets Using Propensity Scores , 1997, Annals of Internal Medicine.

[35]  Joseph L. Gastwirth,et al.  Reference Manual on Scientific Evidence , 1997 .

[36]  Sylvia Richardson,et al.  Markov Chain Monte Carlo in Practice , 1997 .

[37]  D. Rubin,et al.  Bayesian inference for causal effects in randomized experiments with noncompliance , 1997 .

[38]  Geert Molenberghs,et al.  Causal Inference in a Placebo-Controlled Clinical Trial with Binary Outcome and Ordered Compliance , 1996 .

[39]  D B Rubin,et al.  Matching using estimated propensity scores: relating theory to practice. , 1996, Biometrics.

[40]  M. Sobel.  An Introduction to Causal Inference , 1996 .

[41]  David B. Dunson,et al.  Bayesian Data Analysis , 2010 .

[42]  D. Rubin,et al.  In utero exposure to phenobarbital and intelligence deficits in adult men. , 1995, JAMA.

[43]  Clifford C. Clogg,et al.  Handbook of statistical modeling for the social and behavioral sciences , 1995 .

[44]  M. Sobel.  Causal Inference in the Social and Behavioral Sciences , 1995 .

[45]  S G Baker,et al.  The paired availability design: a proposal for evaluating epidural analgesia during labor. , 1994, Statistics in medicine.

[46]  C. Gatsonis.  Case Studies in Bayesian Statistics , 1998 .

[47]  Paul R. Rosenbaum,et al.  Comparison of Multivariate Matching Methods: Structures, Distances, and Algorithms , 1993 .

[48]  Joshua D. Angrist,et al.  Identification of Causal Effects Using Instrumental Variables , 1993 .

[49]  Donald B. Rubin,et al.  Characterizing the effect of matching using linear propensity score methods with normal distributions , 1992 .

[50]  Donald B. Rubin,et al.  Affinely Invariant Matching Methods with Ellipsoidal Distributions , 1992 .

[51]  Charles F. Manski,et al.  Alternative Estimates of the Effect of Family Structure during Adolescence on High School Graduation , 1992 .

[52]  D. Cox.  Causality : some statistical aspects , 1992 .

[53]  B. D. Finetti,et al.  Foresight: Its Logical Laws, Its Subjective Sources , 1992 .

[54]  D. Rubin,et al.  Ignorability and Coarse Data , 1991 .

[55]  P. Rosenbaum.  A Characterization of Optimal Designs for Observational Studies , 1991 .

[56]  Eric P. Fox.  Bayesian Statistics 3 , 1991 .

[57]  B. Efron,et al.  Compliance as an Explanatory Variable in Clinical Trials , 1991 .

[58]  S. Zeger,et al.  On estimating efficacy from clinical trials. , 1991, Statistics in medicine.

[59]  D. Rubin.  [On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9.] Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies , 1990 .

[60]  T. Speed,et al.  On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9 , 1990 .

[61]  A. Gelman,et al.  Estimating Incumbency Advantage Without Bias , 1990 .

[62]  M. Sobel.  Effect analysis and causation in linear structural equation models , 1990 .

[63]  Joseph B. Kadane,et al.  Randomization in a bayesian perspective , 1990 .

[64]  A. Dempster.  Causality and statistics , 1990 .

[65]  Donald B. Rubin,et al.  Formal modes of statistical inference for causal effects , 1990 .

[66]  Paul W. Holland,et al.  Choosing Among Alternative Nonemperimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training: Comment , 1989 .

[67]  Paul W. Holland,et al.  Comment: It's Very Clear , 1989 .

[68]  Paul R. Rosenbaum,et al.  Optimal Matching for Observational Studies , 1989 .

[69]  J. Ware.  Investigating Therapies of Potentially Great Benefit: ECMO , 1989 .

[70]  James J. Heckman,et al.  Causal Inference and Nonrandom Samples , 1989 .

[71]  J. Robins.  The control of confounding by intermediate variables. , 1989, Statistics in medicine.

[72]  James J. Heckman,et al.  Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: the Case of Manpower Training , 1989 .

[73]  Robert Schlaifer,et al.  On the interpretation and observation of laws , 1988 .

[74]  R. Sugden,et al.  Sampling and Assignment Mechanisms in Experiments, Surveys and Observational , 1988 .

[75]  P. Holland.  CAUSAL INFERENCE, PATH ANALYSIS AND RECURSIVE STRUCTURAL EQUATIONS MODELS , 1988 .

[76]  P. Holland.  [Employment Discrimination and Statistical Science]: Comment: Causal Mechanism or Causal Effect: Which Is Best for Statistical Science? , 1988 .

[77]  Arthur P. Dempster,et al.  Employment Discrimination and Statistical Science , 1988 .

[78]  S. Greenland,et al.  Invariants and noninvariants in the concept of interdependent effects. , 1988, Scandinavian journal of work, environment & health.

[79]  P. Holland.  Causal Inference, Path Analysis and Recursive Structural Equations Models. Program Statistics Research, Technical Report No. 88-81. , 1988 .

[80]  D. Rubin.  Multiple imputation for nonresponse in surveys , 1989 .

[81]  D. Rubin,et al.  Statistical Analysis with Missing Data. , 1989 .

[82]  P. Rosenbaum.  The Role of a Second Control Group in an Observational Study , 1987 .

[83]  C. N. Morris,et al.  The calculation of posterior distributions by data augmentation , 1987 .

[84]  R. Prentice,et al.  On the application of linear relative risk regression models. , 1986, Biometrics.

[85]  P. Holland.  Statistics and Causal Inference , 1985 .

[86]  D. Rubin,et al.  Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score , 1985 .

[87]  K E Warner,et al.  Smoking and lung cancer: an overview. , 1984, Cancer research.

[88]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[89]  Howard S. Bloom,et al.  Accounting for No-Shows in Experimental Evaluation Designs , 1984 .

[90]  P. Rosenbaum.  From Association to Causation in Observational Studies: The Role of Tests of Strongly Ignorable Treatment Assignment , 1984 .

[91]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[92]  H. Wainer,et al.  Principals of Modern Psychological Measurement : A Festschrift for Frederic M. Lord , 1983 .

[93]  D. Rubin,et al.  Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome , 1983 .

[94]  Constance Reid.  Neyman from Life , 1982 .

[95]  D. Rubin,et al.  ON LORD'S PARADOX , 1982 .

[96]  P. McCullagh,et al.  Some aspects of analysis of covariance. , 1982, Biometrics.

[97]  Robert Schlaifer,et al.  On the nature and discovery of structure , 1981 .

[98]  M. R. Novick,et al.  The Role of Exchangeability in Inference , 1981 .

[99]  D. Rubin.  Randomization Analysis of Experimental Data: The Fisher Randomization Test Comment , 1980 .

[100]  D. Basu.  Randomization Analysis of Experimental Data: The Fisher Randomization Test , 1980 .

[101]  A. Dawid.  Conditional Independence in Statistical Theory , 1979 .

[102]  M. Zelen.  A new design for randomized clinical trials. , 1979, The New England journal of medicine.

[103]  D. Rubin,et al.  Using Multivariate Matched Sampling and Regression Adjustment to Control Bias in Observational Studies , 1978 .

[104]  Donald B. Rubin,et al.  Bayesian Inference for Causal Effects: The Role of Randomization , 1978 .

[105]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[106]  Donald B. Rubin,et al.  Multivariate matching methods that are equal percent bias reducing , 1974 .

[107]  Donald B. Rubin,et al.  MULTIVARIATE MATCHING METHODS THAT ARE EQUAL PERCENT BIAS REDUCING, I: SOME EXAMPLES , 1974 .

[108]  D. Rubin.  INFERENCE AND MISSING DATA , 1975 .

[109]  D. Rubin.  Estimating causal effects of treatments in randomized and nonrandomized studies. , 1974 .

[110]  John Stuart Mill,et al.  Collected Works of John Stuart Mill , 1974 .

[111]  W. G. Cochran,et al.  Controlling Bias in Observational Studies: A Review. , 1974 .

[112]  D. Rubin.  Matched Sampling for Causal Effects: Matching to Remove Bias in Observational Studies , 1973 .

[113]  Michael D. Geurts,et al.  Time Series Analysis: Forecasting and Control , 1977 .

[114]  W. G. Cochran.  The effectiveness of adjustment by subclassification in removing bias in observational studies. , 1968, Biometrics.

[115]  Michail Prodan,et al.  CHAPTER 17 – THE PLANNING OF EXPERIMENTS , 1968 .

[116]  F. Lord.  A paradox in the interpretation of group comparisons. , 1967, Psychological bulletin.

[117]  Leonid Hurwicz,et al.  On the Structural Form of Interdependent Systems , 1966 .

[118]  John W. Pratt,et al.  Bayesian Interpretation of Standard Inference Statements , 1965 .

[119]  M. Stone,et al.  Studies in Subjective Probability , 1965 .

[120]  J. L. Hodges,et al.  Basic Concepts of Probability and Statistics , 1964 .

[121]  Patrick Suppes,et al.  Logic, Methodology and Philosophy of Science , 1963 .

[122]  H. Chernoff.  Sequential Design of Experiments , 1959 .

[123]  E. C. Hammond,et al.  Smoking and lung cancer: recent evidence and a discussion of some questions. , 1959, Journal of the National Cancer Institute.

[124]  D. Horvitz,et al.  A Generalization of Sampling Without Replacement from a Finite Universe , 1952 .

[125]  Oscar Kempthorne,et al.  The Design and Analysis of Experiments , 1952 .

[126]  E. H. Simpson,et al.  The Interpretation of Interaction in Contingency Tables , 1951 .

[127]  Walter Eucken,et al.  The foundations of economics , 1951 .

[128]  William G. Cochran,et al.  Experimental Designs, 2nd Edition , 1950 .

[129]  F. J. Anscombe,et al.  The Validity of Comparative Experiments , 1948 .

[130]  T. Haavelmo,et al.  The probability approach in econometrics , 1944 .

[131]  M. D. McCarthy.  On the Application of the Z-Test to Randomized Blocks , 1939 .

[132]  E. Pitman.  SIGNIFICANCE TESTS WHICH MAY BE APPLIED TO SAMPLES FROM ANY POPULATIONS III. THE ANALYSIS OF VARIANCE TEST , 1938 .

[133]  B. L. Welch.  ON THE z-TEST IN RANDOMIZED BLOCKS AND LATIN SQUARES , 1937 .

[134]  J. Neyman,et al.  Statistical Problems in Agricultural Experimentation , 1935 .

[135]  J. Neyman.  On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and the Method of Purposive Selection , 1934 .

[136]  J. Mill.  A System of Logic , 1843 .