An extension of an over-dispersion test for count data
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.
Year of publication: |
2011
|
---|---|
Authors: | Baksh, M. Fazil ; Böhning, Dankmar ; Lerdsuwansri, Rattana |
Published in: |
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 55.2011, 1, p. 466-474
|
Publisher: |
Elsevier |
Keywords: | Capture-recapture Over-dispersion Turing estimator Zero-inflation Zero-truncation |
Saved in:
Saved in favorites
Similar items by person
-
A Generalization of Chao's Estimator for Covariate Information
Böhning, Dankmar, (2013)
-
Böhning, Dankmar, (2002)
-
Maximum likelihood estimation of the logarithmic series distribution
Böhning, Dankmar, (1983)
- More ...