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Product details:
- ISBN-10: 1351647970
- ISBN-13: 9781351647977
- Author: Dankmar Bohning
Capture-recapture methods have been used in biology and ecology for more than 100 years. However, it is only recently that these methods have become popular in the social and medical sciences to estimate the size of elusive populations such as illegal immigrants, illicit drug users, or people with a drinking problem. Capture-Recapture Methods for the Social and Medical Sciences brings together important developments which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including topics such as ratio regression models, capture-recapture meta-analysis, extensions of single and multiple source models, latent variable models and Bayesian approaches. The book is suitable for everyone who is interested in applying capture-recapture methods in the social and medical sciences. Furthermore, it is also of interest to those working with capture-recapture methods in biology and ecology, as there are some important developments covered in the book that also apply to these classical application areas.
Table of contents:
1. Basic concepts of capture-recapture
2. Ratio regression and capture-recapture
3. The Conway-Maxwell-Poisson distribution and capture-recapture count data
4. The geometric distribution, the ratio plot under the null and the burden of dengue fever in Chiang Mai province
5. A ratio regression approach to estimate the size of the Salmonella-infected flock population using validation information
6. On meta-analysis in capture-recapture
7. A case study on maritime accidents using meta-analysis in capture -recapture
8. A meta-analytic generalization of the Lincoln–Petersen estimator for mark-and-resight studies
9. Estimating the population size via the empirical probability generating function
10. Convex estimation
11. Non-parametric estimation of the population size using the empirical probability generating function
13. Extensions of the Chao estimator for covariate information: Poisson case
14. Population size estimation for one-inflated count data based upon the geometric distribution
15. Dual and multiple system estimation: Fully observed and incomplete covariates
17. Trimmed dual system estimation
18. Estimation of non-registered usual residents in the Netherlands
19. Population size estimation using a categorical latent variable
20. Latent class: Rasch models and marginal extensions
21. Performance of hierarchical log-linear models for a heterogeneous population with three lists
22. A multidimensional Rasch model for multiple system estimation where the number of lists changes over time
23. Extending the Lincoln–Petersen estimator when both sources are counts
24. Objective Bayes estimation of the population size using Kemp distributions
25. Bayesian population size estimation with censored counts
26. Uncertainty assessment in capture-recapture studies and the choi
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