Publications

Selected Publications

Articles in peer review journals  

1. Robins, J., Rotnitzky, A. and Zhao, L.P.  (1994) Estimation of regression coefficients when some regressors are not always observed. Journal of the American Statistical Association, 89: 846-866

2.   Robins, J., Rotnitzky, A. and Zhao, L.P. (1995).  “Analysis of semiparametric regression models   for repeated outcomes under the presence of missing data.” Journal of the American Statistical Association, 90,106-121.

3. Rotnitzky, A. and Robins, J. (1995).  “Semiparametric regression estimation in the presence of dependent censoring.”  Biometrika, 82, 805-820.

4. Rotnitzky, A. and Robins, J. (1997).  “Analysis of semiparametric regression models with non-ignorable non-response.”   Statistics in Medicine, 16, 81-102.

5.  Rotnitzky, A., Robins, J. and Scharfstein, D. (1998).  “Semiparametric regression for repeated outcomes with non-ignorable non-response.”  Journal of the American Statistical Association, 93, 1321-1339.

6.  Rotnitzky, A., Cox, D.R.,, Bottai, M. and Robins, J. (2000). “Likelihood based inference with singular information matrix.” Bernoulli, 6, 243-284.

7.   Robins, J., Rotnitzky, A., and Van der Laan, M. (2000). “Discussion of the Paper `On Profile Likelihood’ by S. Murphy and A. van der Vaart.”  Journal of the American Statistical Association, 95, 477-482.

8. Rotnitzky, A., Scharfstein, D., Su, T.L. and Robins, J. (2000). “Methods for conducting sensitivity analysis of trials with possibly non-ignorable competing causes of censoring.” Biometrics, 57, 111-121.

9.  Scharfstein, D., Robins, J., Eddings, W. and Rotnitzky, A.  (2001) “Inference in Randomized Studies with Informative Censoring and Discrete Time-to-Event Endpoints.” Biometrics; 57(2):404-413.

10. Schisterman E, Rotnitzky, A. (2001) Estimation of the mean of a K-sample and U-statistic with missing outcomes and auxiliaries. Biometrika; 88:713-725.

11. Robins, J., Rotnitzky, A. (2001) Discussion of a paper by Peter Bickel and Jaimyoung Kwon. Statistica Sinica, 2001; 4: 920-936. (On double-robustness)

12. Birmingham, J., Rotnitzky, A., and Fitzmaurice, G. (2003) “Pattern-mixture and selection models for analyzing monotone missing data” Journal of the Royal Statistical Society, Series B; 65, 275-297

13. Robins, J. and Rotnitzky, A. G. (2004) “Estimation of Treatment Effects in Randomised Trials with Noncompliance and a Dichotomous Outcome using Structural Mean Models.”. Biometrika; 91:763-783

14. Rotnitzky, A., Faraggi, D. and Schisterman, E. (2006). “Doubly-robust estimation of the area under the receiver operating characteristic curve in the presence of verification bias”. Journal of the American Statistical Association: 101, 1276-1288.

15 Rotnitzky, A., Farall, A., Bergesio, A. and Scharfstein, D. (2007) Analysis of failure time data under competing censoring mechanisms. Journal of the Royal Statistical Society, Series B: 69, 307-327

16.  Jemiai, Y., Rotnitzky, A., Shepherd, B., Gilbert, P. (2007).  “Semiparametric Estimation of Treatment Effects Given Baseline Covariates on an Outcome Existing Only if a Post-Randomization Event Occurs”. Journal of the Royal Statistical Society, Series B: 69, 879-901.

17. Vansteelandt, S., Rotnitzky, A. and Robins, J. (2007) “Estimation of regression models for the mean of repeated outcomes under non-ignorable non-monotone non-response”. Biometrika. 94: 841-860

18.  Robins,  J., Hernan, M. and Rotnitzky, A. (2007).  “Effect modification by time varying covariates”.  Discussion of  “History-Adjusted marginal structural models to estimate time-varying effect modification”,  by Petersen M, Deeks S, Martin J, van der Laan M. American Journal of Epidemiology , 166: 994-1002

19.  Robins,  J., Rotnitzky, A. and Vansteelandt, S. (2007).  Discussion of  “Principal stratification designs to impute data missing due to death”, by Frangakis, C., Rubin, D., An, M-W and MacKenzie,  Ellen. Biometrics, 63: 650-653.48.

20.  Robins,  J., Orellana, L. and Rotnitzky, A. (2008). Estimation and extrapolation of optimal treatment and testing strategies. Statistics in Medicine. 27(23):4678-721  

21. Rotnitzky, A., Bergesio, A, and Farall, A. (2009). Analysis of
Quality of Life Adjusted Failure Time Data in the Presence of
Competing, Possibly Informative, Censoring Mechanisms. Lifetime Data Analysis. 15, 1:23

22.   Page, J. and Rotnitzky, A. (2009). Estimation of the disease-specific diagnostic marker di stribution under verification bias. Computational Statistics and Data Analysis. 53 (3) 707-717

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Book Chapters

1.     
1. Robins,
J. and Rotnitzky, A. (1992).
“Recovery of information and adjustment for dependent censoring using surrogate
markers.”  in AIDS Epidemiology; N.P. Jewell, K. Dietz and B. Farewell, eds.
Birkhauser, Boston.

3. 
22. Rotnitzky, A. (1998).  “Efficiency and
Efficient Estimators.”  Encyclopedia of Biostatistics, 2,
1286-1292.

4.     
3. Robins,
J., Rotnitzky, A., Scharfstein,
D. O. (1999) Sensitivity analysis for selection bias and unmeasured confounding
in missing data and causal inference models. In Statistical Models for Epidemiology, the environment, and Clinical
Trials.
E.  Halloran and D Berry,
editors.; IMA Volume 116. NY, Springer-Verlag, pp.1-92.

5.     
4. Rotnitzky, A. G. and Robins, J. (2005) “Inverse Probability Weighted in Survival
Analysis”. The Encyclopedia of Biostatistics. Vol 4. pp. 2619-2625.
Second Edition. Edited by Peter Armitage and Theodore Colton., 2004.

6.     
5. Rotnitzky, A. (2005). “On Semiparametric Inference”.
In
Celebrating
Statistics in honour of Sir David Cox on his 80th birthday
. Edited by Anthony C. Davison, Yadolah Dodge
and Nanny Wermuth. Oxford University Press.

7.      6. Rotnitzky, A. (2008).  Inverse Probability Weighted Methods. In Longitudianal Data Analysis: Modern Statistical Methods. Fitzmauri