Literature DB >> 19067336

Point and interval estimation of the population size using a zero-truncated negative binomial regression model.

Maarten J L F Cruyff1, Peter G M van der Heijden.   

Abstract

This paper presents the zero-truncated negative binomial regression model to estimate the population size in the presence of a single registration file. The model is an alternative to the zero-truncated Poisson regression model and it may be useful if the data are overdispersed due to unobserved heterogeneity. Horvitz-Thompson point and interval estimates for the population size are derived, and the performance of these estimators is evaluated in a simulation study. To illustrate the model, the size of the population of opiate users in the city of Rotterdam is estimated. In comparison to the Poisson model, the zero-truncated negative binomial regression model fits these data better and yields a substantially higher population size estimate. ((c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

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Year:  2008        PMID: 19067336     DOI: 10.1002/bimj.200810455

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  3 in total

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2.  Inferencing superspreading potential using zero-truncated negative binomial model: exemplification with COVID-19.

Authors:  Shi Zhao; Mingwang Shen; Salihu S Musa; Zihao Guo; Jinjun Ran; Zhihang Peng; Yu Zhao; Marc K C Chong; Daihai He; Maggie H Wang
Journal:  BMC Med Res Methodol       Date:  2021-02-10       Impact factor: 4.615

3.  Bayesian analysis of one-inflated models for elusive population size estimation.

Authors:  Tiziana Tuoto; Davide Di Cecco; Andrea Tancredi
Journal:  Biom J       Date:  2022-03-25       Impact factor: 1.715

  3 in total

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