Estimation in captureâ recapture models when covariates are subject to measurement errors and missing data

DOI10.1002/CJS.10038zbMath1191.62033OpenAlexW2020060462MaRDI QIDQ3651434

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Publication date: 10 December 2009

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.10038

zbMATH Keywords

EM algorithmmeasurement errorestimating functionpopulation sizecapture-recapturemissing covariate

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10)

Related Items (7)

A Review of the Use of Conditional Likelihood in Capture-Recapture Experiments ⋮ Estimation of survival and capture probabilities in open population capture-recapture models when covariates are subject to measurement error ⋮ Population size estimation using zero-truncated Poisson regression with measurement error ⋮ Maximum likelihood abundance estimation from capture‐recapture data when covariates are missing at random ⋮ Population size estimation with covariate values missing non-ignorable ⋮ A measurement error model for heterogeneous capture probabilities in mark-recapture experiments: an estimating equation approach ⋮ Approximate estimations in capture–recapture model with heteroscedastic measurement errors

Cites Work

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• Informative Drop-Out in Longitudinal Data Analysis
• A Unified Likelihood‐Based Approach for Estimating Population Size in Continuous‐Time Capture–Recapture Experiments with Frailty
• An Extension of the Cormack–Jolly–Seber Model for Continuous Covariates with Application to Microtus pennsylvanicus
• Measurement Error in Nonlinear Models
• A Generalization of Sampling Without Replacement From a Finite Universe

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