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Semiparametric regression estimation in the presence of dependent censoring
Abstract
We propose a semiparametric estimation procedure for estimating the regression of an outcome Y, measured at the end of a fixed follow-up period, on baseline explanatory variables X, measured prior to start of follow-up, in the presence of dependent censoring given X. The proposed estimators are consistent when the data are ‘missing at random’ but not ‘missing completely at random’ (Rubin, 1976), and do not require full specification of the complete data likelihood. Specifically, we assume that the probability of censoring at time t is independent of the outcome Y conditional on the recorded history up to t of a vector of time-dependent covariates that are correlated with Y. Our estimators can be used to adjust for dependent censoring and nonrandom noncompliance in randomised trials studying the effect of a treatment on the mean of a response variable of interest. Even with independent censoring, our methods allow the investigator to increase efficiency by exploiting the correlation of the outcome with a vector of time-dependent covariates.
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Cites
The Asymptotic Variance of Semiparametric Estimators
Newey, W. K. (1994) · Econometrica · doi:10.2307/2951752 · Cited by 717
Cited by
Recent Developments in the Econometrics of Program Evaluation
Imbens, G. W., & Wooldridge, J. M. (2009) · Journal of Economic Literature · doi:10.1257/jel.47.1.5 · Cited by 4,926
Inverse probability weighted estimation for general missing data problems
Wooldridge, J. M. (2007) · Journal of Econometrics · doi:10.1016/j.jeconom.2007.02.002 · Cited by 1,029
Hirano, K., & Imbens, G. W. (2001) · Health Services and Outcomes Research Methodology · doi:10.1023/a:1020371312283 · Cited by 1,039
Marginal Mean Models for Dynamic Regimes
Murphy, S. A., van der Laan, M. J., Robins, J. M., & Conduct Problems Prevention Research Group (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753382327 · Cited by 393
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Metadata
- Authors
- ROTNITZKY, A., & ROBINS, J. M.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1995
- Volume
- 82
- Issue
- 4
- Pages
- 805-820
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2159927689
- Cited by
- 171
- References
- 1
- FWCI
- 2.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- ROTNITZKY, A., & ROBINS, J. M. (1995). Semiparametric regression estimation in the presence of dependent censoring. Biometrika. https://doi.org/10.1093/biomet/82.4.805
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