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Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations

Robb, Matthew L. and Böhning, Dankmar (2011) Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations Biometrical Journal, 53, (1), pp. 75-87. (doi:10.1002/bimj.201000004).

Record type: Article

Abstract

Capture–recapture techniques have been used for considerable time to predict population size. Estimators usually rely on frequency counts for numbers of trappings; however, it may be the case that these are not available for a particular problem, for example if the original data set has been lost and only a summary table is available. Here, we investigate techniques for specific examples; the motivating example is an epidemiology study by Mosley et al., which focussed on a cholera outbreak in East Pakistan. To demonstrate the wider range of the technique, we also look at a study for predicting the long-term outlook of the AIDS epidemic using information on number of sexual partners. A new estimator is developed here which uses the EM algorithm to impute unobserved values and then uses these values in a similar way to the existing estimators. The results show that a truncated approach – mimicking the Chao lower bound approach – gives an improved estimate when population homogeneity is violated

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More information

e-pub ahead of print date: 24 January 2011
Published date: February 2011
Organisations: Statistics, Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 210471
URI: http://eprints.soton.ac.uk/id/eprint/210471
ISSN: 0323-3847
PURE UUID: b972e440-ecb7-4dfa-be22-012c0847b6ed

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Date deposited: 09 Feb 2012 11:45
Last modified: 18 Jul 2017 10:45

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Contributors

Author: Matthew L. Robb

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