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.)

• VanderWeele TJ, Robins JM. (2012) Stochastic counterfactuals and stochastic sufficient causes. Stochastic counterfactuals and stochastic sufficient causes. Statistica Sinica. 22:279-92.
• Li L, Tchetgen Tchetgen E, van der Vaart, A, Robins JM. (2011). Higher order inference on a treatment effect under low regularity conditions. Statistics and Probability Letters. 81: 821-828.
• Richardson TS, Evans RJ, Robins JM. (2010). Transparent parametrizations of models for potential outcomes. In preliminary papers, Ninth Valencia International Meeting on Bayesian Statistics.
• Richardson TS, Robins JM. (2010). Analysis of the Binary Instrumental Variable Model. Heuristics, Probability and Causality: A Tribute to Judea Pearl H. Geffner and J.Y. Halpern, Editors, College Publications, UK.
• Robins JM, Richardson, TS. (2010). Alternative graphical causal models and the identification of direct effects. To appear in Causality and Psychopathology: Finding the Determinants of Disorders and Their Cures. P. Shrout, Editor. Oxford University Press
• VanderWeele TJ, Robins JM. (2010). Signed directed acyclic graphs for causal inference. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 72(1):111-127.
• Tchetgen Tchetgen E, Robins JM, Rotnitsky A. (2010). On doubly robust estimation in a semiparametric odds ratio model. Biometrika 97(1):171-180.
• Tchetgen Tchetgen E, Robins JM. (2010). The seimiparametric case-only estimator. Biometrics Published on-line; Mar 11, 2010.
• Robins JM, Hernán MA . (2009). In: Estimation of the causal effects of time-varying exposures. Fitzmaurice G, Davidian M, Verbeke G, Molenberghs G, eds. New York: Chapman and Hall/CRC Press, 2009
• Robins JM, Li L, Tchetgen E, van der Vaart A. (2009). Quadratic semiparametric Von Mises calculus. Metrika 69:227-247.
• Robins JM, Tchetgen Tchetgen E, Li L, van der Vaart A. (2009). Semiparametric Minimax Rates. Electron. J. Statist. Volume 3 (2009), 1305-1321.
• Robins JM, Li L, Tchetgen Tchetgen E, van der Vaart A. (2009). Higher order influence functions and minimax estimation of nonlinear functionals. Technical Report July 30, 2009.
• Robins JM, Richardson TS, Spirtes P. (2009). On identification and inference for direct effects. Under revision for Epidemiology November, 2009.
• VanderWeele TJ, Robins JM. (2009). Properties of monotonic effects on Directed Acyclic Graphs. Journal of Machine Learning 10:699-718.
• Hernán MA, Alonso A, Grodstein F, Michels K, Willett W, Manson J, Robins JM. (2008). Observational Studies Analyzed Like Randomized Experiments: Best of Both Worlds. Epidemiology 19(6):789-792.
• Hernán MA, Robins JM. (2008). Authors’ Response, Part I: Observational Studies Analyzed Like Randomized Experiments: An Application to Postmenopausal Hormone Therapy and Coronary Heart Disease. Epidemiology 19(6):766-779.
• VanderWeele TJ, Robins JM. (2008). Minimal sufficient causation and directed acyclic graphs. Annals of Statistics (In Press).
• VanderWeele TJ, Hernán MA, Robins JM. (2008). Causal Directed Acyclic Graphs and the Direction of Unmeasured Confounding Bias. Epidemiology 19(5):720-728.
• Robins JM, Li L, Tchetgen E, van der Vaart A. (2008). Higher order influence functions and minimax estimation of nonlinear functionals. Probability and Statistics: Essays in Honor of David A. Freedman 2:335-421.
• Robins JM. (2008). Causal models for estimating the effects of weight gain on mortality. International Journal of Obesity 32:S15-S41.
• Robins JM, Orellana L, Rotnitzky A. (2008). Estimation and extrapolation of optimal treatment and testing strategies. Statistics in Medicine Jul 21 [Epub ahead of print].
• Kenah E, Lipstich M, Robins JM. (2008). Generation interval contraction and epidemic data analysis. Math Biosci 213(1):71-9.
• Vansteelandt S, Rotnitsky A, Robins JM. (2007). Estimation of regression models for the mean of repeated outcomes under nonignorable nonmonotone nonresponse. Biometrika 94(4):841-860.
• Robins JM, Sued M, Lei-Gomez Q, Rotnitsky A. (2007). Comment: Performance of double-robust estimators when “Inverse Probability” weights are highly variable. Statistical Science 22(4):544-559.
• Cole SR, Hernán MA, Anastos K, Jamieson BD, Robins JM. (2007). Determining the effect of highly active antiretroviral therapy on changes in human immunodeficiency virus type 1 RNA viral load using a marginal structural left-censored mean model. Am J Epidemiology 166(2):219-27.
• VanderWeele TJ, Robins JM. (2007). The identification of synergism in the sufficient-component-cause framework. Epidemiology 18(3):329-39.
• Mills CE, Robins JM, Bergstrom CT, Lipsitch M. (2007). Pandemic influenza: risk of multiple introductions and the need to prepare for them. PLoS Med 3(6):e135.
• Kenah E, Robins JM. (2007). Network-based analysis of stochastic SIR epidemic models with random and proportionate mixing. Journal of Theoretical Biology 249: 706-722.
• Kenah E, Robins JM. (2007). Second look at the spread of epidemics on networks. Physical Review E 76, 036113.
• Robins JM, Rotnitzky A, Vansteelandt S. (2007). Discussion of Principal stratification designs to estimate input data missing due to death. by Frangakis CE, Rubin DB, An M, MacKenzie E. Biometrics 63:650-654
• Robins JM, Hernán MA, Rotnitzky A. (2007). Invited commentary: Effect Modification by Time-varying Covariates.American Journal of Epidemiology published online September 17, 2007
• VanderWeele TJ, Robins JM. (2007). Signed directed acyclic graphs for causal inference. Revised for Journal of the Royal Statistical Society,Series B., in press
• VanderWeele TJ, Robins JM. (2007). The identification of synergism in the sufficient-component cause framework. Epidemiology, 18:329-339.
• VanderWeele TJ, Robins JM. (2007). Four types of effect modification – a classification based on directed acyclic graphs. Epidemiology, 18:561-568.
• VanderWeele TJ, Robins JM. (2007). Directed acyclic graphs, sufficient causes and the properties of conditioning on a common effect. American Journal of Epidemiology,166:1096-1104.
• VanderWeele TJ, Robins JM. (2007). Empirical and counterfactual conditions for sufficient cause interactions. Biometrika, in press.
• Lipsitch M, Robins JM, Mills CE, Bergstrom CT. (2006). Multiple outbreaks and flu containment plans Science 312(5775):875.
• Kurth T, Walker AM, Glynn RJ, Chan KA, Gaziano JM, Berger K, Robins JM. (2006). Results of multivariable logistic regression, propensity adjustment, and propensity-based weighting under conditions of nonuniform effect American Journal of Epidemiology 162(5):471-8
• Robins JM,VanderWeele TJ, Richardson TS. (2006). Comment on causal effects in the presence of non compliance: a latent variable interpretation by Antonio Forcina METRON vol. LXIV(3)288-298.
• Robins JM,Hernán MA. (2006). Instruments for Causal Inference An Epidemiologist’s Dream? Epidemiology 17(4):360-372
• Robins JM,Hernán MA. (2006). Estimating causal effects from epidemiological data.Journal of Epidemiology and Community Health 60:578-586
• Robins J, van der Vaart, A. (2006). Adaptive nonparametric confidence Sets. The Annals of Statistics, 34(1):229-253
• Hernán MA, Lanoy E, Costagliola D, Robins JM. (2006). Comparison of dynamic treatment regimes via inverse probability weighting. Basic & Clinical Pharmacology & Toxicology, 98:237-242
• Cole SR, Hernán MA, Margolick JB, Cohen MH, Robins JM. (2005). Marginal structural models for estimating the effect of highly active antiretroviral therapy initiation American Journal of Epidemiology 162(5):471-8
• Sterne JA, Hernán MA, Ledgergerber B, Tilling K, Weber R, Sendi P, Rickenbach M, Robins JM, Egger M; Swiss HIV Cohort Study. (2005). Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: a prospective cohort study. Lancet 366(9483):378-384
• Glymour MM, Weuve J, Berkman LF, Kawachi I, Robins JM. (2005). When is baseline adjustment useful in analyses of change? An example with education and cognitive change American Journal of Epidemiology 162(3):267-278
• Tchetgen EJ, Li L, Robins JM, van der Vaart A. (2005). Robust Inference with Higher Order Inference Functions: Part I. Proceedings of the Statistics in Epidemiology Section, Joint Statistical Meetings. American Statistical Association
• Li L, Tchetgen EJ, Robins JM, van der Vaart, A. (2005). Robust Inference with Higher Order Inference Functions: Part II. Proceedings of the Statistics in Epidemiology Section, Joint Statistical Meetings. American Statistical Association
• Robins JM, Hernán MA, Garcia Rodriguez LA. (2005). Discussion of statistical issues arising in the women’s health initiative by Prentice RL, Pettinger M, Andreson GL. Biometrics 61:922-930
• Bang H, Robins J. (2005). Doubly robust estimation in Missing data and causal inference models. Biometrics, 61:692-972.
• Hernán MA, Cole S, Margolick J, Cohen M, Robins J (2005). Structural accelerated failure time models for survival analysis in studies with time-varying treatments. Pharmacoepidemiology and Drug Safety. (Published online 19 Jan 2005)
• Andrews C, van der Lann M, Robins J (2005). Locally efficient estimation of regression parameters using current status data. Journal of Multivariate Analysis (to appear).
• Robins J, Hernán MA, and Siebert U. Edited by  Ezzati, M. and Murray, C.J.L. and Lopez, A.D. and Rodgers, A. Effects of multiple interventions. In: Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors. Chapter 28; Vol 2.  World Health Organization, Geneva. (2004): 2191-2230.
• Robins JM (2004). Optimal structural nested models for optimal sequential decisions. In DY Lin and P Heagerty (Eds.), Proceedings of the Second Seattle Symposium on Biostatistics , New York. Springer. Erratum to
• Hernán MA, Hernandez Diaz S. and Robins JM (2004). A structural approach to selection bias. Epidemiology, 15: 615-625.
• Robins JM. (2004). Should compensation schemes be based on the probability of causation or expected years of life lost? Journal of Law and Policy 12(2): 537-548.
• Newey WK, Hseih F, Robins, JM. (2004). Twicing kernels and a small bias property of semiparametric estimators. Econometrica 72(3) 947-962.
• Freedman DA, Petitti DB, Robins JM. (2004). On the efficacy of screening for breast cancer. International Journal of Epidemiology, 33:43-55. Comment by Gotzsche PC. On the benefits and harms of screening for breast cancer,pp. 56-64. Comment by Miller AB. Commentary: A defence of the Health Insurance Plan (HIP) study and the Canadian National Breast Screening Study (CNBSS) pp. 64-65. Comment by Baum M. Commentary: False premises, false promises and false positives – the case against mammographic screening for breast cancer. pp. 66-67. Comment by Berry D. Commentary: Screening mammography: a decision analysis. pp. 68. Rejoinder by Freedman DA, Petitti DB, Robins JM.Rejoinder. pp. 69-73.
• Robins JM, Rotnitzky A. (2004). Estimation of treatment effects in randomised trials with non-compliance and a dichotomous outcome using structural mean models. Biometrika 91: 763-783.
• Liang H, Wang S, Robins JM, Carroll RJ. (2004). Estimation in partially linear models with missing covariates. Journal of the American Statistical Association, 99(466):357-67
• Brumback BA, Hernán MA, Haneuse SJPA, Robins JM. (2004). Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures Statistics in Medicine, 23:749-767.
• Lok J, Gill R, van der Vaart A, Robins J. (2004). Estimating the causal effect of a time-varying treatment on time-to-event using structural nested failure time models. Statisca Neerlandica, 58(3):271-295.
• Robins JM, Scheines R, Spirtes P, and Wasserman L. (2003). Uniform consistency in causal inference. Biometrika, 90(3):491-515.
• van der Laan MJ, Robins JM. (2003). Unified Methods for Censored Longitudinal Data and Causality. Springer Verlag: New York. Click here to purchase.
• Robins JM. (2003). Semantics of causal DAG models and the identification of direct and indirect effects. In Highly Structured Stochastic Systems, P. Green, N.L. Hjort, S. Richardson, Editors. NY: Oxford University Press, pp. 70-81.
• Rotnitzky A, Robins JM. (2003). Inverse probability weighted estimation in survival analysis. To appear in The Encyclopedia of Biostatistics.
• Cole SR, Hernán MA, Robins JM, Anastos K, Chmiel J, Detels R, Ervin C, Feldman J, Greenblatt R, Kingsley L, Lai S, Young M, Cohen M, Munoz A. (2003). Effect of highly active antiretroviral therapy on time to acquired immunodeficiency syndrome or death using marginal structural models. American Journal of Epidemiology, 158(7):687-694.
• Robins JM, Scheines R, Spirtes P, and Wasserman L. (2003). Uniform consistency in causal inference. Biometrika, 90(3):491-515.
• Robins JM. (2003). Discussion of “A theory of statistical models for Monte Carlo integration”. by Kong A, McCullagh P, Meng X-L, Nicolae D, Tan Z. Journal of the Royal Statistical Society: Series B, 65(3):585-618.
• Robins JM. (2003). Discussion of “Optimal dynamic treatment regimes”. by Susan A. Murphy. Journal of the Royal Statistical Society: Series B, 65(2):355-366.
• Robins JM. (2003). General methodological considerations. Journal of Econometrics, 112(1):89-106.
• Robins JM. (2003). Semantics of causal DAG models and the identification of direct and indirect effects. In: Highly Structured Stochastic Systems, Eds by P. Green, N. Hjort and S. Richardson, Oxford University Press.
• Scharfstein DO, Daniels MJ, Robins JM. (2002). Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes. Biostatistics, 4(4):495-512.
• Robins JM. (2002). Comment on “Covariance adjustment in randomized experiments and observational studies.”. by Paul R. Rosenbaum. Statistical Science, 17(3):286-327.
• Scharfstein DO, Robins JM. (2002). Estimation of the failure time distribution in the presence of informative censoring”. Biometrika, 89(3):617-634.
• Hernán MA, Brumback B, Robins JM. (2002). Estimating the causal effect of zidovudine on CD4 count with a marginal structural model for repeated measures. Statistics in Medicine, 21:1689-1709.
• Robins JM. (2002). Commentary on “Using inverse weighting and predictive inference to estimate the effects of time-varying treatments on the discrete-time hazard”. by Dawson and Lavori. Statistics in Medicine, 21:1663-1680.
• van der Laan MJ, Hubbard AE, Robins JM. (2002). Locally efficient estimation of a multivariate survival function in longitudinal studies. Journal of the American Statistical Association, 97(458):494-507.
• Choi HK, Hernán MA, Seeger JD, Robins JM, Wolfe F. (2002). Methotrexate and mortality in patients with rheumatoid arthritis: a prospective study. The Lancet, 359:1173-77.
• Murphy SA, van der Laan MJ, Robins JM, CPPRG (2001). Marginal mean models for dynamic regimes. Journal of the American Statistical Associataion. 96(456):1410-1423.
• Robins JM, Smoller JW, Lunetta K (2001). On the validity of the TDT test in the presence of comorbidity and ascertainment bias. Genetic Epidemiology. 21(4):326-36.
• Gill RD, Robins JM. (2001). Causal inference for complex longitudinal data: the continuous case. To appear in Annals of Statistics. (click here for reference to figure one)
• Hernán M, Brumback B, Robins JM. (2001). Marginal structural models to estimate the joint causal effect of nonrandomized treatments. Journal of the American Statistical Association — Applications and Case Studies, 96(454):440-448.
• Robins JM. (2001). Data, design, and background knowledge in etiologic inference. Epidemiology, 11(3):313-320.
• Rotnitzky A, Scharfstein D, Su T-L, Robins JM. (2001). Methods for Conducting Sensitivity Analysis of Trials with Potentially Nonignorable Competing Causes of Censoring. Biometrics, 57(1):103-113.
• Robins JM, Rotnitzky A. (2001). Comment on the Bickel and Kwon article, “Inference for semiparametric models: Some questions and an answer” Statistica Sinica, 11(4):920-936. [“On Double Robustness.”]
• Robins JM, Rotnitzky A, and Bonetti M. (2001). Discussion of the Frangakis and Rubin article, “Addressing an idiosyncrasy in estimating survival curves using double sampling in the presence of self-selected right censoring.” Biometrics, 57(2):343-347.
• Satten GA, Datta S, Robins JM. (2001). Estimating the marginal survival function in the presence of time dependent covariates. (to appear, Statistics & Probability Letters).
• Scharfstein DO, Robins JM, Eddings W, Rotnitzky A. (2001). Inference in randomized studies with informative censoring and discrete time-to-event endpoints. Biometrics, 57(2):404-413.
• Smoller JW, Lunetta K, Robins JM (2000). Implications of Comorbidity and ascertainment bias for identifying disease genes. American Journal of Medical Genetics (Neuropsychiatric Genetics). 96:817-822.
• Breslow NE, Robins JM, Wellner JA (2000). On the semiparametric efficiency of logistic regression under case-control sampling. Bernoulli. 6(3):447-455.
• Rotnitzky A, Cox DR, Bottai M, Robins J M (2000). Likelihood-based inference with singular information matrix. Bernoulli. 6(2):243-284.
• Scharfstein DO, Robins JM (2000). Non/Semi-Parametric Estimation of the Failure Time Distribution in the Presence of Informative Censoring. Submitted to Biometrika. (Click here and then on link to paper.)

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.)

• Hernán M, Brumback B, Robins JM. (2000). Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology, 11(5):561-570.
• Robins JM, Rotnitzky, A. (2000). Estimation in missing data models. International Biometric Society: The XXth International Biometric Conference, Volume II, Invited program: pp. 153-162.
• Robins JM. (2000). Robust estimation in sequentially ignorable missing data and causal inference models. Proceedings of the American Statistical Association Section on Bayesian Statistical Science 1999, pp. 6-10.
• Robins JM, Finkelstein D. (2000). Correcting for Non-compliance and Dependent Censoring in an AIDS Clinical Trial with Inverse Probability of Censoring Weighted (IPCW) Log-rank Tests Biometrics, 56(3):779-788.
• Robins JM, Hernán M, Brumback B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5):550-560.
• Robins JM, Greenland S. (2000). Comment on “Causal Inference Without Counterfactuals” by A.P. Dawid. Journal of the American Statistical Association — Theory and Methods, 95(450):477-482.
• Robins JM, Rotnitzky A, van der Laan M. (2000). Comment on “On Profile Likelihood” by S.A. Murphy and A.W.van der Vaart. Journal of the American Statistical Association — Theory and Methods, 95(450):431-435.
• Robins JM, van der Vaart A, Ventura V. (2000). The Asymptotic Distribution of P-Values in Composite Null Models. Journal of the American Statistical Association, 95(452):1143-1156. Comments, Journal of the American Statistical Association, 95(452):1157-1167. Rejoinder by Bayarri and Berger, Journal of the American Statistical Association, 95(452):1168-1170. Rejoinder by Robins, van der Vaart and Ventura, Journal of the American Statistical Association, 95(452):1171-1172.
• Robins JM, Wang N. (2000). Inference for imputation estimators. Biometrika, 87(1):113-124.
• Robins JM, Wasserman L. (2000). Conditioning, likelihood, and coherence: A review of some foundational concepts. Journal of the American Statistical Association, 95(452):1340-1346.
• Greenland S, Robins JM. (2000). Epidemiology, justice, and the probability of causation. Jurimetrics, 40(3):321-340.
• Greenland S, Robins JM, Pearl J. (1999). Confounding and collapsibility in causal inference. Statistical Science, 14(1): 29-46.
• Keiding N, Filiberti M, Esbjerg S, Robins JM, Jacobsen N. (1999). The Graft Versus Leukemia Effect after Bone Marrow Transplantation: A Case Study Using Structural Nested Failure Time Models. Biometrics. 55(1): 23-29.
• Robins JM. (1999). Association, causation, and marginal structural models. Synthese, 121:151-179.
• Robins JM. (1999). Comment on “Choice as an Alternative to Control in Observational Studies” by Paul Rosenbaum. Statistical Science, 14(3):281-293.
• Greenland S, Pearl J, Robins JM. (1999). Causal diagrams for epidemiologic research. Epidemiology, 10(1):37-48.
• Robins JM. (1999). Testing and estimation of direct effects by reparameterizing directed acyclic graphs with structural nested models. In: Computation, Causation, and Discovery. Eds. C. Glymour and G. Cooper. Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, pp. 349-405. For further information on this book from The MIT Press, please click here.
• Robins JM. (1999). Marginal Structural Models versus Structural Nested Models as Tools for Causal Inference. Statistical Models in Epidemiology: The Environment and Clinical Trials. M.E. Halloran and D. Berry, Editors, IMA Volume 116, NY: Springer-Verlag, pp. 95-134.
• Robins JM, Greenland S, Hu F-C. (1999). Estimation of the causal effect of a time-varying exposure on the marginal mean of a repeated binary outcome. Journal of the American Statistical Association – Applications and Case Studies, 94:687-700. Reproduced courtesy of the American Statistical Association.
• Robins JM, Greenland S, Hu F-C. (1999). Rejoinder to Comments on “Estimation of the causal effect of a time-varying exposure on the marginal mean of a repeated binary outcome.” Journal of the American Statistical Association, Applications and Case Studies, 94:708-712. Reproduced courtesy of the American Statistical Association.
• Robins JM, Rotnitzky A, Scharfstein D. (1999). Sensitivity Analysis for Selection Bias and Unmeasured Confounding in Missing Data and Causal Inference Models. In: Statistical Models in Epidemiology: The Environment and Clinical Trials. Halloran, M.E. and Berry, D., eds. IMA Volume 116, NY: Springer-Verlag, pp. 1-92.
• Scharfstein DO, Rotnitzky A, Robins JM. (1999). Adjusting for non-ignorable drop-out using semiparametric non-response models. Journal of the American Statistical Association, 94:1096-1120. Comments and Rejoinder, Journal of the American Statistical Association, 94:1121-1146. Reproduced courtesy of the American Statistical Association.
• Robins JM, Wasserman L. (1999). On the impossibility 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. 305-321.

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.

• Joffe MM, Hoover DR, Jacobson LP, Kingsley L, Chmiel JS, Fischer BR, Robins JM (1998). Estimating the effect of Ziduvodine on Kaposi’s sarcoma from observational data using a rank preserving failure time model. Statistics in Medicine. 17:1073-1102.
• Robins JM. (1998). Correction for non-compliance in equivalence trials. Statistics in Medicine, 17:269-302.
• Robins JM. (1998). Marginal structural models. 1997 Proceedings of the American Statistical Association. Section on Bayesian Statistical Science, pp. 1-10. Reproduced courtesy of the American Statistical Association.
• Robins JM, Wang N. (1998). Discussion on the papers by Forster and Smith and Clayton et al. Journal of the Royal Statistical Society B, 60(Part 1):91-93.
• Rotnitzky A, Robins JM, Scharfstein D. (1998). Semiparametric regression for repeated outcomes with nonignorable nonresponse. Journal of the American Statstical Association, 93(444):1321-1339.
• Van der Laan MJ, Robins JM. (1998). Locally efficient estimation with current status data and time-dependent covariates. Journal of the American Statistical Association, 93:693-701. Reproduced courtesy of the American Statistical Association.
• Wang N, Robins JM. (1998). Large-sample theory for parametric multiple imputation procedures. Biometrika (to appear).
• Witteman JC, d’Agostino RB, Stijnen T, Kannel WB, Cobb JC, deRidder MAJ, Hoffman A, Robins JM. (1998). G-estimation of causal effects: isolated systolic hypertension and cardiovascular death in the Framingham Study.American Journal of Epidemiology, 148:390-401. Reproduced courtesy of the American Journal of Epidemiology.
• Garcia-Closas M, Thompson WD, Robins JM. (1998). Differential misclassifications and the assessment of gene-enviornment interactions.American Journal of Epidemiology, 147(5):426-433.
• Robins JM. (1998). Discussion of “Quantifying Surprise in the data and model verification” by Bayarri MJ and Berger JO..Bayesian Statistics 6, Eds. Bernardo JM, Berger JO, Dawid AP and Smith AFM. Oxford, UK: Oxford University Press. pp 67-70
• Rotnitzky A, Holcroft C, Robins JM (1997). Efficiency comparisons in multivariate multiple regression with missing outcomes. Journal of Multivariate Analysis. 61:102-128.
• Scharfstein DO, Tsiatis AA, Robins JM (1997). Semiparametric efficiency and its implication on the design and analysis of group sequential studies. Journal of the American Statistical Association. 92(44): 1342-1350.
• Gill RD, van der Laan MJ, Robins JM. (1997). Coarsening at random: characterizations, conjectures and counterexamples. Proceedings of the First Seattle Symposium on Survival Analysis, pp. 255-294.
• Gill RD, Robins JM. (1997). Sequential Models for Coarsening and missingness. Proceedings of the First Seattle Symposium on Survival Analysis, pp. 295-305.
• Robins JM. (1997). Causal Inference from Complex Longitudinal Data. Latent Variable Modeling and Applications to Causality. Lecture Notes in Statistics (120), M. Berkane, Editor. NY: Springer Verlag, pp. 69-117.
• Robins JM. (1997). Non-response models for the analysis of non-monotone non-ignorable missing data. Statistics in Medicine, 16:21-37.
• Robins JM. (1997). Structural nested failure time models. In: Survival Analysis, P.K. Andersen and N. Keiding, Section Editors. The Encyclopedia of Biostatistics, P. Armitage and T. Colton, Editors. Chichester, UK: John Wiley & Sons, pp. 4372-4389.
• Robins JM, Gill R. (1997). Non-response models for the analysis of non-monotone ignorable missing data. Statistics in Medicine, 16:39-56.
• Robins JM, Ritov Y. (1997). Toward a curse of dimensionality appropriate (CODA) asymptotic theory for semi-parametric models. Statistics in Medicine, 16:285-319.
• Robins JM, Wasserman L. (1997). Estimation of Effects of Sequential Treatments by Reparameterizing Directed Acyclic Graphs. Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, Providence Rhode Island, August 1-3, 1997. Dan Geiger and Prakash Shenoy (Eds.), Morgan Kaufmann, San Francisco, pp. 409-420.
• Rotnitzky A, Robins JM. (1997). Analysis of semiparametric regression models with non-ignorable non-response. Statistics in Medicine, 16:81-102.
• Holcroft CA, Rotnitzky A, Robins JM (1997). Efficient estimation of regression parameters from multistage studies with validation of outcome and covariates. Journal of Statistical Planning and Inference. 65:349-374.
• Michels KB, Robins JM, Willett WC (1997). Response to “Birthweight as a risk factor”. The Lancet. 349:502.
• Lin DY, Robins JM, Wei LJ. (1996). Comparing two failure time distributions in the presence of dependent censoring. Biometrika, 83:381-393.
• Robins JM, Gill RD.(1996). Non-response models for the analysis of non-monotone ignorable missing data. Statistics in Medicine, 16:39-56.
• Robins JM. (1996). Estimating the causal effect of a time-varying treatment on survival using structural nested failure time models. Statistica Nederlandica (to appear).
• Robins JM, Greenland S. (1996). Comment on Angrist, Imbens and Rubin: Estimation of the global average treatment effects using instrumental variables. Journal of the American Statistical Association, 91:456-458.
• Robins JM. (1996). Locally Efficient Median Regression With Random Censoring and Surrogate Markers.Proceedings of the 1994 Conference on Lifetime Data Models in Reliability and Survival Analysis, Boston, MA. In:Lifetime Data: Models in Reliability and Survival Analysis, N.P. Jewell et al., Eds., Kluwer Academic Publishers, 263-274.
• Michels KB, Trichopoulos D, Robins JM, Rosner BA, Manson JE, Hunter DJ, Colditz GA, Hankinson SE, Speizer FE, Willett WC. (1996). Birthweight as a risk factor for breast cancer. The Lancet, 348:1542-1546.
• Pearl J, Robins JM. (1995). Probabilistic evaluation of sequential plans from causal models with hidden variables. Uncertainty in Artificial Intelligence, Proceedings of the 11th Conference, pp. 444-453. Click here for a direct link or click here and go to Report Number R-219-U to view paper.
• Robins JM. (1995). An analytic method for randomized trials with informative censoring: Part I. Lifetime Data Analysis, 1:241-254.
• Robins JM. (1995). An analytic method for randomized trials with informative censoring: Part II. Lifetime Data Analysis, 1:417-434.
• Robins JM. (1995). Comments on Judea Pearl’s paper, “Causal diagrams for empirical research”. Biometrika, 82:695-698.
• Robins JM. and Rotnitzky, A. (1995). Semiparametric efficiency in multivariate regression models with missing data. Journal of the American Statistical Association, 90:122-129. Reproduced courtesy of the American Statistical Association.
• Robins JM, Rotnitzky A, Zhao L-P. (1995). Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. Journal of the American Statistical Association, 90:106-121.
• Rotnitzky A, Robins JM. (1995). Semiparametric regression estimation in the presence of dependent censoring. Biometrika, 82:805-820.
• Mittleman MA, Maclure M, Robins JM (1995). Control Sampling Strategies for Case-Crossover Studies: An Assessment of Relative Efficiency. American Journal of Epidemiology. 142(1):91-98.
• Robins JM, Hsieh F, Newey W (1995). Semiparametric efficient estimation of a conditional density with missing or mismeasured covariates. Journal of the Royal Statistical Society, Series B. 57(2):409-424.
• Rotnitzky A, Robins JM. (1995). Semi-parametric estimation of models for means and covariances in the presence of missing data. Scandanavian Journal of Statistics, 22:323-333.
• Greenland S, Robins JM. (1994). Invited commentary: Ecologic studies-biases, misconceptions, and counterexamples [comment]. American Journal of Epidemiology, 139:747-760; and Greenland S.,Robins, J.M. (1994). Accepting the limits of ecologic studies: Drs. Greenland and Robins reply to Drs. Piantadosi and Cohen. American Journal of Epidemiology, 139:769-771.
• Robins JM. (1994). Correcting for non-compliance in randomized trials using structural nested mean models. Communications in Statistics, 23:2379-2412.
• Robins JM. , Greenland S. (1994). Adjusting for differential rates of PCP prophylaxis in high- versus low-dose AZT treatment arms in an AIDS randomized trial. Journal of the American Statistical Association, 89:737-749. Reproduced courtesy of the American Statistical Association.
• Robins JM, Rotnitzky A, Zhao LP. (1994). Estimation of regression coefficients when some regressors are not always observed. Journal of the American Statistical Association, 89:846-866. Reproduced courtesy of the American Statistical Association.
• Robins JM,(1994). Limits of epidemiological evidence and uncertainty analysis in occupational risk assessment. Chemical Risk Analysis and Occupational Health: Current Applications, Limitations, and Future Prospects, Westport, CT:Auburn House pp181-186.
• Mark SD, Robins JM. (1993). Estimating the causal effect of smoking cessation in the presence of confounding factors using a rank preserving structural failure time model.Statistics in Medicine, 12:1605-1628.
• Mark SD, Robins JM. (1993). A method for the analysis of randomized trials with compliance information: An application to the multiple risk factor intervention trial. Controlled Clinical Trials. New York: Elsevier. 14:79-97.
• Robins JM. (1993).Analytic methods for estimating HIV treatment and cofactor effects. Methodological Issues of AIDS Mental Health Research. Eds: Ostrow D.G., Kessler R. New York: Plenum Publishing. pp. 213-290. Reproduced with permission of Plenum Publishing.
• Pugh M, Robins, JM, Lipsitz S, Harrington D. (1993). Inference in the Cox Proportional Hazards Model with Missing Covariates. Technical Report, Harvard School of Public Health, Department of Biostatistics.
• Robins JM. (1993). Information recovery and bias adjustment in proportional hazards regression analysis of randomized trials using surrogate markers Proceedings of the Biopharmaceutical Section, American Statistical Association, pp. 24-33. Reproduced courtesy of the American Statistical Association.
• Mark S, Robins JM. (1993). A method for the analysis of randomized trials with compliance information: An application to the multiple risk factor intervention trial Controlled Clinical Trials, pp. 24-33. Reproduced courtesy of the American Statistical Association..
• Robins JM. (1992). Estimation of the time-dependent accelerated failure time model in the presence of confounding factors. Biometrika, 79:321-34.
• Robins JM, Blevins D, Ritter G, Wulfsohn M. (1992). G-estimation of the effect of prophylaxis therapy for pneumocystis carinii pneumonia on the survival of AIDS patients. Epidemiology, 3:319-336. Please see also the following link for the Errata to the article: Robins, J.M., Blevins D, Ritter G., and Wulfsohn M. (1993). Errata to G-estimation of the effect of prophylaxis therapy for pneumocystis carinii pneumonia on the survival of AIDS patients. Epidemiology, 14:79-97.
• Robins JM , Greenland S. (1992). Identifiability and exchangeability for direct and indirect effects. Epidemiology, 3:143-155. Reproduced with permission of the publisher, Lippincott, Williams and Wilkins.
• Robins JM, Mark SD, Newey WK. (1992). Estimating exposure effects by modelling the expectation of exposure conditional on confounders. Biometrics, 48:479-495.
• Robins JM, Rotnitzky A. (1992). Recovery of information and adjustment for dependent censoring using surrogate markers. AIDS Epidemiology – Methodological Issues. Eds: Jewell N., Dietz K., Farewell V. Boston, MA: Birkhäuser. pp. 297-331 (includes errata sheet).
• Robins JM, Tsiatis AA. (1992). Semiparametric estimation of an accelerated failure time model with time-dependent covariates. Biometrika, 79:311-319.
• Greenland S, Robins JM, (1991). Empirical-Bayes adjustments for multiple comparisons are sometimes useful. Epidemiology, 2:244-251.
• Robins JM, Tsiatis A. (1991). Correcting for non-compliance in randomized trials using rank-preserving structural failure time models. Communications in Statistics, 20:2609-2631.
• Robins JM, Greenland S. (1991). Estimability and estimation of years of life lost due to a hazardous exposure. Statistics in Medicine, 10:79-93.
• Lagakos SW, LIN L-Y, Robins JM, (1990). Adjusting for early treatment termination in comparative clinical trials. Statistics in Medicine, 9:1417-1427.
• Pike MC, Robins JM. (1989). RE: “Possibility of selection bias in matched case-control studies using friend controls”. American Journal of Epidemiology. 130:209-210.
• Robins JM. (1989). The analysis of randomized and non-randomized AIDS treatment trials using a new approach to causal inference in longitudinal studies. Health Service Research Methodology: A Focus on AIDS. Eds: Sechrest L., Freeman H., Mulley A. Washington, D.C.: U.S. Public Health Service, National Center for Health Services Research.,pp. 113-159. Please see also the following link for the Errata to the article: ERRATA for The analysis of randomized and non-randomized AIDS treatment trials using a new approach to causal inference in longitudinal data.
• Robins JM. (1989). The control of confounding by intermediate variables. Statistics in Medicine, 8:679-701.
• Robins JM, Greenland S. (1989). Estimability and estimation of excess and etiologic fractions. Statistics in Medicine, 8:845-859.
• Robins JM, Greenland S. (1989). The probability of causation under a stochastic model for individual risk. Biometrics, 45:1125-1138.
• Robins JM, Prentice RL, Blevins D(1989). Designs for synthetic case-control studies in open cohorts. Biometrics. 45:1103-1116.
• Robins JM, Blevins D(1989). The effective number of cigarettes inhaled by passive smokers: are epidemiologic and dosimetric methods consistent? Journal of Hazardous Materials. 21:215-238.
• Robins JM, Pambrun M, Chute C, Blevins D. (1988). Estimating the effect of formaldehyde exposure on lung cancer and non-malignant respiratory disease (NMRD) mortality using a new method to control the healthy worker survivor effect. Progress in Occupational Epidemiology. Eds: C. Hogstedt C. and C. Reuterwall C. New York: Elsevier, pp. 75-79.
• Robins JM. (1988). “The limits of epidemiological data in determining the probability of causation and years of life lost when exposures and covariates are time-varying”. Technical Report #37. Harvard School of Public Health, Department of Biostatistics.
• Robins JM. (1988). Confidence intervals for causal parameters.Statistics in Medicine, 7:773-785.
• Walker AM, Velema JP, Robins JM. (1988). Analysis of case-control data derived in part from proxy respondents.American Journal of Epidemiology 127:905-914.
• Greenland S, Robins JM. (1988). Conceptual problems in the definition and interpretation of attributable fractions.American Journal of Epidemiology 128:1185-1197.
• Robins JM. and Morgenstern H. (1987). The foundations of confounding in epidemiology. Computers and Mathematics with Applications, 14:869-916 (includes errata sheet).
• Robins JM. (1987). A graphical approach to the identification and estimation of causal parameters in mortality studies with sustained exposure periods.Journal of Chronic Disease (40, Supplement), 2:139s-161s.
• Robins JM, Blevins D. (1987). Analysis of proportionate mortality data using logistic regression models.American Journal of Epidemiology 125:524-535.
• Robins J. (1986). Risk assessment: Exposure to environmental tobacco smoke and lung cancer.Environmental Tobacco Smoke. Washington, DC: National Academy of Sciences, pp. 294-337.. 123(3): 392-402.
• Robins J, Greenland S. (1986). The role of model selection in causal inference from nonexperimental data. American Journal of Epidemiology. 123(3): 392-402.
• Robins J, Greenland S, Breslow N. (1986). A general estimator for the varience of the Mantel-Haenszel odds ratio. American Journal of Epidemiology. 124(5): 719-723.
• Robins JM. (1986). A new approach to causal inference in mortality studies with sustained exposure periods – Application to control of the healthy worker survivor effect. Mathematical Modelling, 7:1393-1512, with 1987 Errata to “A new approach to causal inference in mortality studies with sustained exposure periods – Application to control of the healthy worker survivor effect.” Computers and Mathematics with Applications, 14:917-921; 1987 Addendum to “A new approach to causal inference in mortality studies with sustained exposure periods – Application to control of the healthy worker survivor effect.” Computers and Mathematics with Applications, 14:923-945; and 1987 Errata to “Addendum to ‘A new approach to causal inference in mortality studies with sustained exposure periods – Application to control of the healthy worker survivor effect’.” Computers and Mathematics with Applications, 18:477.
• Robins JM, Gail M, Lubin J (1986). More on biased selection of controls for case-control analysis of cohort studies. Biometrics. 42:293-299.
• Robins JM, Breslow N, Greenland S (1986). Estimators of the Mantel-Haenszel variance consistent in both sparse data and large-strata limiting models. Biometrics. 42:311-323.
• Greenland S, Robins JM (1986). Identifiability, exchangeability and epidemiological confounding. International Journal of Epidemiology. 15:413-419.
• Louis TA, Robins JM, Dockery DW, Spiro A, Ware JH (1986). Explaining discrepancies between longitudinal and cross-sectional models. Journal of Chronic Diseases. 39:831-839.
• Greenland S, Robins JM (1985). Estimation of a common effect parameter from sparse follow-up data. Biometrics. 41:55-68.
• Greenland S, Robins JM (1985). Confounding and misclassification. American Journal of Epidemiology. 122:495-506.
• Robins JM, Landrigan PJ, Robins TG, Fine LJ (1985). Decision-making under uncertainty in the setting of enviornmental health regulations. Journal of Public Health Policy. 6(3):322-328.
• Thomas DC, Siemiatycki J, Dewar R, Robins JM, Goldberg M, Armstrong BG (1985). The problem of multiple inference in studies designed to generate hypotheses. American Journal of Epidemiology. 122:1080-1095.
• Cullen MR, Kayne RD, Robins JM. (1984). Endocrine and reproductive dysfunction in men associated with occupational inorganic lead intoxication. Archives of Environmental Health. 39:431-441.

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