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Logistic Regression in Capture-Recapture Models
Abstract
The effect of population heterogeneity in capture-recapture, or dual registration, models is discussed. An estimator of the unknown population size based on a logistic regression model is introduced. The model allows different capture probabilities across individuals and across capture times. The probabilities are estimated from the observed data using conditional maximum likelihood. The resulting population estimator is shown to be consistent and asymptotically normal. A variance estimator under population heterogeneity is derived. The finite-sample properties of the estimators are studied via simulation. An application to Finnish occupational disease registration data is presented.
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Cited by
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Large scale wildlife monitoring studies: statistical methods for design and analysis
Pollock, K. H., Nichols, J. D., Simons, T. R., Farnsworth, G. L., Bailey, L. L., & Sauer, J. R. (2002) · Environmetrics · doi:10.1002/env.514 · Cited by 684
Winter prey selection and estimation of wolf kill rates in Yellowstone National Park, 1995–2000
SMITH, D. W., DRUMMER, T. D., MURPHY, K. M., GUERNSEY, D. S., & EVANS, S. B. (2004) · Journal of Wildlife Management · doi:10.2193/0022-541x(2004)068[0153:wpsaeo]2.0.co;2 · Cited by 191
Metadata
- Authors
- Alho, J. M.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1990-09
- Volume
- 46
- Issue
- 3
- Pages
- 623
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2327380363
- Cited by
- 219
- References
- 0
- FWCI
- 3.83
- Type
- journal article
- Language
- en
- Open access
- closed
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- Alho, J. M. (1990). Logistic Regression in Capture-Recapture Models. Biometrics. https://doi.org/10.2307/2532083
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