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A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data
Abstract
An approach to covariate analysis of current status data is described. The method is applicable when the logit of the conditional probability of survival given the covariates is some increasing function of time plus a linear combination of the covariates. The approach is based on approximating the infinite-dimensional nuisance parameter, the baseline log-odds of failure, with a step function, and carrying out a maximum likelihood procedure. The resulting finite dimensional parameter estimates for the regression parameters are shown to be asymptotically normal and semiparametric efficient. Numerical studies with small and moderate samples are discussed.
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Citations
Cited by
Royston, P., & Parmar, M. K. B. (2002) · Statistics in Medicine · doi:10.1002/sim.1203 · Cited by 1,529
Murphy, S. A., & Van Der Vaart, A. W. (2000) · Journal of the American Statistical Association · doi:10.1080/01621459.2000.10474219 · Cited by 712
Maximum Likelihood Estimation in the Proportional Odds Model
Murphy, S. A., Rossini, A. J., & van der Vaart, A. W. (1997) · Journal of the American Statistical Association · doi:10.1080/01621459.1997.10474051 · Cited by 276
Self-citationFlexible Parametric Alternatives to the Cox Model, and more
Royston, P. (2001) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0100100101 · Cited by 259
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
- Rossini, A. J., & Tsiatis, A. A.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1996-06
- Volume
- 91
- Issue
- 434
- Pages
- 713-721
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W1965761093
- Cited by
- 187
- References
- 0
- FWCI
- 5.15
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rossini, A. J., & Tsiatis, A. A. (1996). A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1996.10476939
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
