Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.csda.2010.05.015 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
over-dispersion,existing test,residual over-dispersion,zero-truncation,test procedure,capture-recapture study,un-truncated count data,over-dispersion test,zero-truncated count data,test statistic,capture–recapture,turing estimator,zero-inflation,zero-inflated count data,zero-inflation data,asymptotic distribution,count data,population size,over dispersion,capture recapture | Econometrics,Residual,Overdispersion,Test statistic,Count data,Statistics,Asymptotic analysis,Sample size determination,Statistical hypothesis testing,Mathematics,Asymptotic distribution | Journal |
Volume | Issue | ISSN |
55 | 1 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
1 | 0.39 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Fazil Baksh | 1 | 2 | 0.78 |
| Dankmar Böhning | 2 | 50 | 13.62 |
| Rattana Lerdsuwansri | 3 | 1 | 0.39 |