Effective use of multiple error-prone covariate measurements in capture-recapture models

Kun Xu, Yanyuan Ma

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We study capture-recapture models in a closed population when multiple error-prone measurements of a covariate are available. Due to the identity between the number of captures and the number of measurements, no suitable complete and sufficient statistic exists, and the existing method no longer applies. The familiar strategy of generalized method of moments fails to resolve this issue satisfactorily, and complexity lies in the loss of the surrogacy assumption commonly assumed in measurement error problems. Our approach to this problem through a semiparametric treatment overcomes these difficulties. The superior performance of the new method is demonstrated through numerical experiments in simulated and data examples.

Original languageEnglish (US)
Pages (from-to)1529-1546
Number of pages18
JournalStatistica Sinica
Volume24
Issue number4
DOIs
StatePublished - Oct 1 2014

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Capture-recapture
Measurement Error
Covariates
Generalized Method of Moments
Sufficient Statistics
Resolve
Numerical Experiment
Closed
Model
Measurement error
Strategy
Sufficient statistics
Numerical experiment
Generalized method of moments

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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Effective use of multiple error-prone covariate measurements in capture-recapture models. / Xu, Kun; Ma, Yanyuan.

In: Statistica Sinica, Vol. 24, No. 4, 01.10.2014, p. 1529-1546.

Research output: Contribution to journalArticle

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