Bohning D., van der Heijden P.G.M., Bunge J. Capture-recapture methods for the social and medical sciences

New York: Chapman and Hall/CRC Press, 2017. — 430 p. — (Interdisciplinary Statistics Series). — ISBN: 978-1-4987-4531-4.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 area.Basic concepts of capture-recapture
Ratio Regression Models
Ratio regression and capture-recapture
The Conway–Maxwell–Poisson distribution and capture-recapture count data
The geometric distribution, the ratio plot under the null and the burden of dengue fever in Chiang Mai province
A ratio regression approach to estimate the size of the Salmonella-infected ock population using validation information
Meta-Analysis in Capture-Recapture
On meta-analysis in capture-recapture
A case study on maritime accidents using meta-analysis in capture-recapture
A meta-analytic generalization of the Lincoln–Petersen estimator for mark-and-resight studies
Extensions of Single Source Models
Estimating the population size via the empirical probability generating function
Convex estimation
Non-parametric estimation of the population size using the empirical probability generating function
Extending the truncated Poisson regression model to a time-at-risk model
Extensions of the Chao estimator for covariate information: Poisson case
Population size estimation for one-inated count data based upon the geometric distribution
Multiple Sources
Dual and multiple system estimation: Fully observed and incomplete covariates
Population size estimation in CRC models with continuous covariates
Trimmed dual system estimation
Estimation of non-registered usual residents in the Netherlands
Latent Variable Models
Population size estimation using a categorical latent variable
Latent class: Rasch models and marginal extensions
Performance of hierarchical log-linear models for a heterogeneous population with three lists
A multidimensional Rasch model for multiple system estimation
Extending the Lincoln–Petersen estimator when both sources are counts
Bayesian Approaches
Objective Bayes estimation of the population size using Kemp distributions
Bayesian population size estimation with censored counts
Miscellaneous Topics
Uncertainty assessment in capture-recapture studies and the choice of sampling effort