 An extension of an over-dispersion test for count dataM. Fazil Baksh, Dankmar Böhning and Rattana Lerdsuwansri Computational Statistics & Data Analysis, 2011, vol. 55, issue 1, 466-474 Abstract: While over-dispersion in capture-recapture studies is well known to lead to poor estimation of population size, current diagnostic tools to detect the presence of heterogeneity have not been specifically developed for capture-recapture studies. To address this, a simple and efficient method of testing for over-dispersion in zero-truncated count data is developed and evaluated. The proposed method generalizes an over-dispersion test previously suggested for un-truncated count data and may also be used for testing residual over-dispersion in zero-inflation data. Simulations suggest that the asymptotic distribution of the test statistic is standard normal and that this approximation is also reasonable for small sample sizes. The method is also shown to be more efficient than an existing test for over-dispersion adapted for the capture-recapture setting. Studies with zero-truncated and zero-inflated count data are used to illustrate the test procedures. Keywords: Capture-recapture; Over-dispersion; Turing; estimator; Zero-inflation; Zero-truncation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:55:y:2011:i:1:p:466-474 Access Statistics for this article Computational Statistics & Data Analysis is currently edited by S.P. Azen More articles in Computational Statistics & Data Analysis from Elsevier |
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