D B Rubin

Summary

Affiliation: Harvard University
Country: USA

Publications

  1. ncbi request reprint More powerful randomization-based p-values in double-blind trials with non-compliance
    D B Rubin
    Department of Statistics, Harvard University, Cambridge, MA 02138, USA
    Stat Med 17:371-85; discussion 387-9. 1998
  2. ncbi request reprint The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials
    Donald B Rubin
    Department of Statistics, Harvard University, 1 Oxford Street, 7th Floor, Cambridge, MA 02138, USA
    Stat Med 26:20-36. 2007
  3. pmc Reflections stimulated by the comments of Shadish (2010) and West and Thoemmes (2010)
    Donald B Rubin
    Harvard University, Cambridge, MA 02138, USA
    Psychol Methods 15:38-46. 2010
  4. ncbi request reprint The ethics of consulting for the tobacco industry
    D B Rubin
    Department of Statistics, Harvard University, Cambridge, MA 02138, USA
    Stat Methods Med Res 11:373-80. 2002
  5. ncbi request reprint Estimating the causal effects of smoking
    D B Rubin
    Department of Statistics, Harvard University, 1 Oxford Street, Cambridge, MA 02138, USA
    Stat Med 20:1395-414. 2001
  6. ncbi request reprint Intermittent degradation in performance in schizophrenia
    S Matthysse
    Department of Psychiatry, Harvard Medical School, Boston, MA, USA
    Schizophr Res 40:131-46. 1999
  7. doi request reprint Testing treatment effects in unconfounded studies under model misspecification: logistic regression, discretization, and their combination
    M Z Cangul
    Department of Statistics, Harvard University, Science Center, Cambridge, MA 02138 2901, USA
    Stat Med 28:2531-51. 2009
  8. ncbi request reprint Principal stratification in causal inference
    Constantine E Frangakis
    Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland 21205, USA
    Biometrics 58:21-9. 2002
  9. ncbi request reprint On principles for modeling propensity scores in medical research
    Donald B Rubin
    Pharmacoepidemiol Drug Saf 13:855-7. 2004
  10. ncbi request reprint Diagnostics for confounding in PK/PD models for oxcarbazepine
    Jerry R Nedelman
    Biostatistics and Statistical Reporting, Novartis Pharmaceuticals, East Hanover, NJ 07936, USA
    Stat Med 26:290-308. 2007

Collaborators

Detail Information

Publications12

  1. ncbi request reprint More powerful randomization-based p-values in double-blind trials with non-compliance
    D B Rubin
    Department of Statistics, Harvard University, Cambridge, MA 02138, USA
    Stat Med 17:371-85; discussion 387-9. 1998
    ..It is important to note that these new procedures are distinctly different from 'as treated' and 'per protocol' analyses, which are not only badly biased in general, but generally have very low power...
  2. ncbi request reprint The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials
    Donald B Rubin
    Department of Statistics, Harvard University, 1 Oxford Street, 7th Floor, Cambridge, MA 02138, USA
    Stat Med 26:20-36. 2007
    ..The collection of these subgroups then 'approximate' a randomized block experiment with respect to the observed covariates...
  3. pmc Reflections stimulated by the comments of Shadish (2010) and West and Thoemmes (2010)
    Donald B Rubin
    Harvard University, Cambridge, MA 02138, USA
    Psychol Methods 15:38-46. 2010
    ....
  4. ncbi request reprint The ethics of consulting for the tobacco industry
    D B Rubin
    Department of Statistics, Harvard University, Cambridge, MA 02138, USA
    Stat Methods Med Res 11:373-80. 2002
    ..To me, it is entirely appropriate to present the application of this academic work in a legal setting...
  5. ncbi request reprint Estimating the causal effects of smoking
    D B Rubin
    Department of Statistics, Harvard University, 1 Oxford Street, Cambridge, MA 02138, USA
    Stat Med 20:1395-414. 2001
    ....
  6. ncbi request reprint Intermittent degradation in performance in schizophrenia
    S Matthysse
    Department of Psychiatry, Harvard Medical School, Boston, MA, USA
    Schizophr Res 40:131-46. 1999
    ..We discuss ways of detecting dialipsis and comparing the mixture model statistically with alternative models...
  7. doi request reprint Testing treatment effects in unconfounded studies under model misspecification: logistic regression, discretization, and their combination
    M Z Cangul
    Department of Statistics, Harvard University, Science Center, Cambridge, MA 02138 2901, USA
    Stat Med 28:2531-51. 2009
    ..This flaw is not corrected by the commonly used technique of discretizing the covariate into intervals. A valid test can be obtained by discretization followed by regression adjustment within each interval...
  8. ncbi request reprint Principal stratification in causal inference
    Constantine E Frangakis
    Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland 21205, USA
    Biometrics 58:21-9. 2002
    ..We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority...
  9. ncbi request reprint On principles for modeling propensity scores in medical research
    Donald B Rubin
    Pharmacoepidemiol Drug Saf 13:855-7. 2004
  10. ncbi request reprint Diagnostics for confounding in PK/PD models for oxcarbazepine
    Jerry R Nedelman
    Biostatistics and Statistical Reporting, Novartis Pharmaceuticals, East Hanover, NJ 07936, USA
    Stat Med 26:290-308. 2007
    ..It was necessary to demonstrate the similarity of the true PK/PD relationships of adults and children on adjunctive therapy in order to support the approval of oxcarbazepine monotherapy in children by a bridging argument...
  11. ncbi request reprint Principal stratification designs to estimate input data missing due to death
    Constantine E Frangakis
    Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland 21205, USA
    Biometrics 63:641-9; discussion 650-62. 2007
    ..Thus, our approach suggests that the routine collection of data on variables that could be used as possible treatments in such studies of inputs and mortality should become common...
  12. ncbi request reprint Control of confounding through secondary samples
    Li Yin
    Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Box 281, SE17177, Stockholm, Sweden
    Stat Med 25:3814-25. 2006
    ..For illustration, we use a formal example of a generalized linear model and a real example with sparse data from a case-control study of the association between gastric cancer and HM-CAP/Band 120...