The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Efficient estimation for the proportional hazards model with interval censoring
Open accessAbstract
The maximum likelihood estimator (MLE) for the proportional hazards model with "case 1" interval censored data is studied. It is shown that the MLE for the regression parameter is asymptotically normal with $\sqrt{n}$ convergence rate and achieves the information bound, even though the MLE for the baseline cumulative hazard function only converges at $n^{1/3}$ rate. Estimation of the asymptotic variance matrix for the MLE of the regression parameter is also considered. To prove our main results, we also establish a general theorem showing that the MLE of the finite-dimensional parameter in a class of semiparametric models is asymptotically efficient even though the MLE of the infinite-dimensional parameter converges at a rate slower than $\sqrt{n}$. The results are illustrated by applying them to a data set from a tumorigenicity study.
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Regression Models and Life-Tables
Cox, D. R. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00899.x · Cited by 39,793
Regression Models and Life-Tables
Cox, D. R. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4380-9_37 · Cited by 26,297
Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,796
Rockafellar, R. T. (1970) · Princeton University Press eBooks · doi:10.1515/9781400873173 · Cited by 10,801
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,525
Weak Convergence and Empirical Processes
van der Vaart, A. W., & Wellner, J. A. (1996) · Springer Series in Statistics · doi:10.1007/978-1-4757-2545-2 · Cited by 5,014
Cox’s regression model for counting processes: A large sample study
Andersen, P. K., & Gill, R. D. (1982) · The Annals of Statistics · doi:10.1214/aos/1176345976 · Cited by 4,419
Statistical Models Based on Counting Processes
Bry, X., Andersen, P. K., Borgan, Ø., Gill, R. D., Keiding, N., & Borgan, O. (1997) · Population (French Edition) · doi:10.2307/1534625 · Cited by 2,884
Statistical Models Based on Counting Processes
Andersen, P. K., Borgan, Ø., Gill, R. D., & Keiding, N. (1993) · Springer Series in Statistics · doi:10.1007/978-1-4612-4348-9 · Cited by 2,855
A Course in Probability Theory
(1974) · Elsevier eBooks · doi:10.1016/c2009-0-22097-6 · Cited by 2,668
Cited by
Murphy, S. A., & Van Der Vaart, A. W. (2000) · Journal of the American Statistical Association · doi:10.1080/01621459.2000.10474219 · Cited by 712
Risk prediction with imperfect survival outcome information from electronic health records
Hou, J., Chan, S. F., Wang, X., & Cai, T. (2023) · Biometrics · doi:10.1111/biom.13599 · Cited by 7
Metadata
- Authors
- Huang, J.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 1996-04-01
- Volume
- 24
- Issue
- 2
- Pages
- 540-568
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W2064207173
- Cited by
- 448
- References
- 26
- FWCI
- 8.71
- Type
- journal article
- Language
- en
- Open access
- bronze
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