Misclassification of current status data
Open Access
- 16 February 2010
- journal article
- research article
- Published by Springer Nature in Lifetime Data Analysis
- Vol. 16 (2) , 215-230
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
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