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Lifetime Data Analysis

, Volume 16, Issue 2, pp 215–230 | Cite as

Misclassification of current status data

  • Karen McKeown
  • Nicholas P. Jewell
Open Access
Article

Abstract

We describe a simple method for nonparametric estimation of a distribution function based on current status data where observations of current status information are subject to misclassification. Nonparametric maximum likelihood techniques lead to use of a straightforward set of adjustments to the familiar pool-adjacent-violators estimator used when misclassification is assumed absent. The methods consider alternative misclassification models and are extended to regression models for the underlying survival time. The ideas are motivated by and applied to an example on human papilloma virus (HPV) infection status of a sample of women examined in San Francisco.

Keywords

Current status data Misclassification 

Notes

Acknowledgments

The authors wish to thank Dr. B. Moscicki for permission to use the HPV data, obtained with support from the National Institute of Health through grant #R37-CA51323. We also acknowledge support for this research from the National Institute of Allergy and Infectious Diseases through grant #R01-ES015493.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

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Copyright information

© The Author(s) 2010

Authors and Affiliations

  1. 1.Division of Biostatistics, School of Public HealthUniversity of CaliforniaBerkeleyUSA

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