The objective of this project is the further development of new non and semi-parametric methods for the analysis of health studies with missing data and censored data. The main emphasis is in the development of inferential methods that make the most effective use of the observed data under models that make minimal assumptions about the full data law and the censoring or missingness mechanism. ? ? The first aim is to develop a general methodology for the analysis of non-ignorable informative right censored data with possibly competing types of censoring that will allow the analyst to appropriately adjust for informative censoring due to measured factors while simultaneously quantifying the sensitivity of the inference to residual dependence of the outcome of interest and censoring due to unmeasured factors. The methods will be applied to the analysis of failure time data, quality of life adjusted survival data, medical cost data and, more generally, to inference about a function of an increasing stochastic process with a randomly stopped censored stopping time.
The second aim i s to develop methods of inference about the mean of a K-sample U-statistic with missing data. These methods will be applied to derive corrections to the Mann-Whitney distribution free test and to estimate the area under the receiving operator characteristic curves of diagnostic tests obtained from studies with selective ascertainment of disease status.
The third aim i s to develop new pattern mixture models for longitudinal incomplete data which assume semi or non-parametric models for the distribution of the missing data in each stratum of non-response.
The fourth aim i s to develop semiparametric methods for the analysis of complex study designs with follow-up of non-respondents. The fifth aim is to develop the theory of doubly-robust estimation and to construct doubly-robust estimators in missing data problems. Doubly robust estimators are attractive because they remain consistent and asymptotically normal under misspecification of either (but not both) the model for the missingness mechanism or the model for the distribution of the full data.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM048704-11
Application #
6775613
Study Section
Special Emphasis Panel (ZRG1-SNEM-5 (01))
Program Officer
Whitmarsh, John
Project Start
1994-01-01
Project End
2006-07-31
Budget Start
2004-08-01
Budget End
2006-07-31
Support Year
11
Fiscal Year
2004
Total Cost
$324,000
Indirect Cost
Name
Harvard University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
02115
Wang, Lu; Rotnitzky, Andrea; Lin, Xihong et al. (2012) Rejoinder to comments on Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer. J Am Stat Assoc 107:518-520
Lok, Judith J; DeGruttola, Victor (2012) Impact of time to start treatment following infection with application to initiating HAART in HIV-positive patients. Biometrics 68:745-54
Wang, Lu; Rotnitzky, Andrea; Lin, Xihong et al. (2012) Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer. J Am Stat Assoc 107:493-508
Tchetgen Tchetgen, Eric J; Rotnitzky, Andrea (2011) Double-robust estimation of an exposure-outcome odds ratio adjusting for confounding in cohort and case-control studies. Stat Med 30:335-47
Hu, Tianle; Nan, Bin; Lin, Xihong et al. (2011) Time-dependent cross ratio estimation for bivariate failure times. Biometrika 98:341-354
Tchetgen Tchetgen, E J; Rotnitzky, A (2011) On protected estimation of an odds ratio model with missing binary exposure and confounders. Biometrika 98:749-754
Lok, Judith J; Bosch, Ronald J; Benson, Constance A et al. (2010) Long-term increase in CD4+ T-cell counts during combination antiretroviral therapy for HIV-1 infection. AIDS 24:1867-76
Rotnitzky, Andrea; Li, Lingling; Li, Xiaochun (2010) A note on overadjustment in inverse probability weighted estimation. Biometrika 97:997-1001
Tchetgen Tchetgen, Eric J; Robins, James M; Rotnitzky, Andrea (2010) On doubly robust estimation in a semiparametric odds ratio model. Biometrika 97:171-180
Wang, Lu; Rotnitzky, Andrea; Lin, Xihong (2010) Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations. J Am Stat Assoc 105:1135-1146

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