Feb 19, 2004

Estimation in capture-recapture models when covariates are subject to measurement errors

Biometrics
Wen-Han Hwang, Steve Y H Huang

Abstract

We consider estimation problems in capture-recapture models when the covariates or the auxiliary variables are measured with errors. The naive approach, which ignores measurement errors, is found to be unacceptable in the estimation of both regression parameters and population size: it yields estimators with biases increasing with the magnitude of errors, and flawed confidence intervals. To account for measurement errors, we derive a regression parameter estimator using a regression calibration method. We develop modified estimators of the population size accordingly. A simulation study shows that the resulting estimators are more satisfactory than those from either the naive approach or the simulation extrapolation (SIMEX) method. Data from a bird species Prinia flaviventris in Hong Kong are analyzed with and without the assumption of measurement errors, to demonstrate the effects of errors on estimations.

Mentioned in this Paper

In Silico
Prinia flaviventris
School Age Population
Sample Size
Aves
Refractive Errors
Biometry
Hong Kong Zebrafish
Two-Parameter Models
Probability

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