Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations |
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Authors: | Robb Matthew L Böhning Dankmar |
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Affiliation: | Department of Mathematics, South Kensington Campus, Imperial College London, London SW7 2AZ, UK. m.robb09@imperial.ac.uk |
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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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Keywords: | Capture–recapture Censoring and truncation for count data Cholera outbreak EM algorithm |
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