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Capture-recapture studies with incomplete mixed categorical and continuous covariates

Capture-recapture studies with incomplete mixed categorical and continuous covariates
Capture-recapture studies with incomplete mixed categorical and continuous covariates
Registrations in epidemiological studies suffer from incompleteness, thus a general consensus is to use capture-recapture models. Inclusion of covariates which relate to the capture probabilities has been shown to improve the estimate of population size. The covariates used have to be measured by all the registrations. In this article, we show how multiple imputation can be used in the capture-recapture problem when some lists do not measure some of the covariates or alternatively if some covariates are unobserved for some individuals. The approach is then applied to data on neural tube defects from the Netherlands.
1680-743X
573-589
Zwane, E.
fe3d004f-61cb-4580-8680-a942d2dbcd04
van der Heijden, P.G.M.
85157917-3b33-4683-81be-713f987fd612
Zwane, E.
fe3d004f-61cb-4580-8680-a942d2dbcd04
van der Heijden, P.G.M.
85157917-3b33-4683-81be-713f987fd612

Zwane, E. and van der Heijden, P.G.M. (2008) Capture-recapture studies with incomplete mixed categorical and continuous covariates. Journal of Data Science, 6 (4), 573-589.

Record type: Article

Abstract

Registrations in epidemiological studies suffer from incompleteness, thus a general consensus is to use capture-recapture models. Inclusion of covariates which relate to the capture probabilities has been shown to improve the estimate of population size. The covariates used have to be measured by all the registrations. In this article, we show how multiple imputation can be used in the capture-recapture problem when some lists do not measure some of the covariates or alternatively if some covariates are unobserved for some individuals. The approach is then applied to data on neural tube defects from the Netherlands.

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More information

Published date: October 2008
Organisations: Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 344684
URI: http://eprints.soton.ac.uk/id/eprint/344684
ISSN: 1680-743X
PURE UUID: 0743be7c-90c3-4aa8-bc00-66c2a8fb401f
ORCID for P.G.M. van der Heijden: ORCID iD orcid.org/0000-0002-3345-096X

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Date deposited: 26 Oct 2012 15:29
Last modified: 23 Feb 2023 03:00

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Contributors

Author: E. Zwane

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