Bibliography

Papers available through Dr. Robins’ Web Site: (in Acrobat format)
(The manuscripts listed below [with links] are available through the Web Site. For reprints/preprints of manuscripts not available through the Web Site, please contact Dr. Robins at 617/432-0206; email: robins@hsph.harvard.edu.)

Scharfstein DO, Robins JM (2000). Non/Semi-Parametric Estimation of the Failure Time Distribution in the Presence of Informative Censoring: Technical Appendix. (Click here and then on link to paper.)

C. Glymour, P. Spirtes, and T. Richardson, “On the possibility of inferring causation from association without background knowledge,” In: Computation, Causation, and Discovery. Eds. C. Glymour and G. Cooper. Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, pp. 323-331, in response to Robins’ and Wasserman’s article, “On the impossibility of inferring causation from association without background knowledge,” may be found here.
Robins JM, Wasserman L. (1999). Rejoinder to Glymour and Spirtes. In: Computation, Causation, and Discovery. Eds. C. Glymour and G. Cooper. Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, pp. 333-342.
C. Glymour, P. Spirtes, and T. Richardson “Response to Rejoinder,” In: Computation, Causation, and Discovery. Eds. C. Glymour and G. Cooper. Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, pp. 343-345, may be found here.

Complete Listing of Published Papers and Papers Accepted for Publication

(Only the papers listed above are available through the Web Site.)

  • Murphy S, van der Laan M, Robins JM, CPPRG. (2001) Marginal mean models for dynamic regimes. Journal of the American Statistical Association, 96(456):1410-1423.
  • Robins JM. (2000) Towards a formal theory of causation in ecologic and multi-level studies (to appear, Journal of the Royal Statistical Society).
  • Hubbard A, van der Laan MJ, Robins JM. (1999) Nonparametric locally efficient estimation of the treatment specific survival distributions with right censored data and covariates in observational studies. In: Statistical Models in Epidemiology: The Environment and Clinical Trials. Halloran, E. and Berry, D., eds., IMA Volume 116, NY: Springer-Verlag, pp. 135-178.
  • Robins JM. (1999) Discussion of “Quantifying surprise in the data and model verification” by Bayarri, M.J. and Berger, J.O. In: Bayesian Statistics 6. Eds. Bernardo, J.M., Dawid, A.P., and Smith, A.F.M. Oxford, UK:Oxford University Press, pp. 67-70.
  • Robins JM. (1997). Discussion of the Paper by Copas and Li. p. 89.
  • Garcia-Closas M, Thompson WD, Robins JM. (1997). Differential misclassification and the assessment of gene-environment interactions in case-control studies. American Journal of Epidemiology (to appear).
  • Holcroft CA, Rotnitzky A, Robins JM. (1997). Efficient estimation of regression parameters from multistage studies with validation of outcome and covariates. J. Stat. Plann. Inf. (to appear).
  • Robins JM, Greenland S. (1996) Comment. Journal of the American Statistical Association, 91:456-458.
  • Robins JM, Rotnitzky A. (1996) Estimating regression coefficients in the presence of dependent censoring. Tentatively accepted, Journal of the American Statistical Association – Theory and Methods, (to appear).
  • Robins JM, Hsieh F-S, Newey W. (1995) Semiparametric efficient estimation of a conditional density with missing or mismeasured covariates. Journal of the Royal Statistical Society, B, 57:409-424.
  • Rotnitzky A, Robins JM. (1995) Semi-parametric estimation of models for means and covariances in the presence of missing data. Scandinavian Journal of Statistics, 22:[323]-333.
  • Robins JM. (1991). Estimating regression coefficients in the presence of dependent censoring. Tentatively accepted, Journal of the American Statistical Association – Theory and Methods.
  • Robins JM, Pike M. (1990). The validity of case-control studies with nonrandom selection of controls. Epidemiology, (1)4:273-284.
  • Osterman JW, Greaves IA, Smith TJ, Hammond SK, Robins JM, Theriault G. (1989). Respiratory symptoms associated with low level sulphur dioxide exposure in silicon carbide production workers. British Journal of Industrial Medicine, 46:629-635.
  • Osterman JW, Greaves IA, Smith TJ, Hammond SK, Robins JM, Theriault G. (1989). Work related decrement in pulmonary function in silicon carbide production workers. British Journal of Industrial Medicine, 46:708-716.
  • Struchiner CJ, Halloran ME, Robins JM., Spielman A. (1989). The behaviour of common measures of association used to access a vaccination program under complex disease transmission patterns – a computer simulation study of malaria vaccines. International Journal of Epidemiology, 19:187-196.
  • Robins JM, Cullen M, Welch LS. (1987) Improved methods for discerning the health impacts of current technologies. Invited Paper, Council on Environmental Quality Conference on Human Health Impacts and Their Mitigation, Washington, DC, September 1984. Environmental Impacts on Human Health: An Agenda for Long Term Research and Development. Eds. Draggan S., et al. New York: Praeger Press, pp. 165-191.
  • Swan SH, Robins JM. (1986) Comment. Journal of the American Statistical Association, 81(395):604-609.
  • Robins JM, Landrigan PJ, Robins TG, Fine LJ. (1985). Decision-making under uncertainty in the setting of environmental health regulations. Journal of Public Health Policy, 6(3):322-328.
  • Robins JM, Cullen MR, Connors B.B., and Kayne R.D. (1982). Depressed thyroid indexes associated with occupational exposure to inorganic lead. Archives of Internal Medicine, 143:220-224.

Papers Submitted for Publication and Papers in Preparation

  • Scharfstein DO, Daniels M, Robins JM. (2001). Incorporating model uncertainty into the analysis of randomized trials with non-compliance (in preparation).
  • Robins JM. (2000). Robust estimation in sequentially ignorable missing data and causal inference models (submitted to Proceedings of the American Statistical Association).
  • Scharfstein DO, Robins JM, Rotnitzky A, Eddings W. (2000). Causal Inference in Randomized Studies with Informative Censoring and Discrete Time-to-Event Outcomes. (Biometrics, under review).
  • Newey W, Hsieh F, Robins JM. (1998). Undersmoothing and bias corrected functional estimation (submitted to Econometrica).
  • Robins JM, Greenland S. (1998). Estimation of Effects of Time-varying Treatments (in preparation).
  • Robins JM, Scheines R, Spirtes P, Wasserman L. (1998). The limits of causal knowledge (in preparation).
  • Scharfstein DO, Robins JM. (1998). Semiparametric bivariate location-shift model for failure time data in the presence of informative censoring (in preparation).
  • Robins JM, Wasserman L. (1998). Estimation of effects of time-varying treatments (in preparation).
  • Hubbard A, van der Laan MJ, Robins JM. (1997/1998). Estimation of the survival distribution among treatment groups with right-censored data and covariates in observational studies (in preparation).
  • Rotnitzky A, Scharfstein D, Su T-L, Robins JM. (1998). Sensitivity analysis of a randomized trial with non-ignorable non-compliance and drop-out (in preparation).
  • Gill RD, van der Laan MJ, Robins JM. (1996). Locally efficient estimation in censored data models with high dimensional covariate vectors or time-dependent marker processes (submitted).
  • Robins JM and Rotnitzky A. (1995). Information recovery and bias adjustment in proportional hazards regression using surrogate markers (submitted to Biometrika).
  • Robins JM. (1993). A least squares approach to information recovery in proportional hazards regression using surrogate markers (submitted to Journal of the American Statistical Association).
  • Hu F-C, Robins JM. Using limit laws for Markov chains to estimate the causal effect of a time-varying exposure on a repeated binary outcome. Technical Report, Department of Epidemiology, Harvard School of Public Health (submitted to Biometrics).
  • Pugh M, Robins JM., Lipsitz, S., and Harrington, D. (1993). Inference in the Cox Proportional Hazards Model with Missing Covariates. Technical Report, Harvard School of Public Health, Department of Biostatistics.

Course Notes

Semantics of Causal DAG Models

Sequential Randomized Trial of AZT and AP on Survival

Methods for Causal Inference from Observational Data (I)

Picture for Jamie’s Biased(I)

Problems

Final Exam Epi 207a 2000

Instrumental Variables