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Cited by 276

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

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

Abstract

We consider maximum likelihood estimation of the parameters in the proportional odds model with right-censored data. The estimator of the regression coefficient is shown to be asymptotically normal with efficient variance. The maximum likelihood estimator of the unknown monotonic transformation of the survival time converges uniformly at a parametric rate to the true transformation. Estimates for the standard errors of the estimated regression coefficients are obtained by differentiation of the profile likelihood and are shown to be consistent. A likelihood ratio test for the regression coefficient is also considered.

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Crossref · 10.1080/01621459.1997.10474051

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Metadata

Authors
Murphy, S. A., Rossini, A. J., & van der Vaart, A. W.
Venue
Journal of the American Statistical Association
Published
1997-09
Volume
92
Issue
439
Pages
968-976
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
OpenAlex
W2016681503
Cited by
276
References
15
FWCI
6.84
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Maximum Likelihood Estimation in the Proportional Odds Model. https://app.cochat.ai/papers/10.1080/01621459.1997.10474051
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Murphy, S. A., Rossini, A. J., & van der Vaart, A. W. (1997). Maximum Likelihood Estimation in the Proportional Odds Model. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1997.10474051

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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.