46
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

Consistency of the non-parametric maximum pseudo-likelihood estimator of the disease onset distribution function for a survival–sacrifice model

Pages 39-46 | Received 01 Jan 2006, Published online: 18 Feb 2008
 

Abstract

Suppose that in a carcinogenicity experiment with animals where the tumour is not palpable, we observe only the time of death of the animal, the cause of death (the tumour or another independent cause, as sacrifice) and whether the tumour was present at the time of death. These last two indicator variables are evaluated after an autopsy. We can estimate the cumulative distribution function F 2 of the time of death from the disease using the Kaplan–Meier estimator and then calculate the non-parametric maximum pseudo-likelihood estimator (NPMPLE) of the cumulative distribution function F 1 of the time of onset of the disease. After a brief review of some past works on the estimation of F 1 and F 2, we demonstrate the strong uniform consistency of the NPMPLE of F 1.

Acknowledgements

The author is grateful to two anonymous referees for their constructive comments which have contributed to the substantial improvement of the paper.

Additional information

Notes on contributors

A.E. Gomes

Email: [email protected]

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 912.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.