Chapman and Hall/CRC
430 pages | 82 B/W Illus.
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.
"This is a timely, important book on the use of capture-recapture methods for social and medical data. … Several books have been written on capture-recapture methods for ecology, over many years, and one focussing on social and medical applications has been long overdue. … This book illustrates the power of appropriate capture-recapture analyses in areas other than ecology. Several of the book chapters describe new methods, and suggest avenues for future research. … The relevance of the methods described is evident, with applications to studies of the prevalence of scrapie, and estimating numbers of injecting drug users, of immigrants, and of victims of domestic violence, etc. Time and again we see the power of Statistics in providing answers to really important questions….
I enjoyed reading this book enormously. A great attraction is the wide range of motivating examples, complete with data, which include several from ecology. The way that methods are regularly illustrated on both real and simulated data is engrossing. Models are clearly described and accessible. The book should be required reading, for years to come, for any university course on Applied Statistical Modeling, as well as being a vital reference for research. I am sure that this book will be much read, and make a major impact."
—From the Foreword by Byron J. T. Morgan
I Introductory Part
Basic concepts of capture-recapture - Dankmar Bohning, John Bunge, and Peter G.M. van der Heijden
II Ratio Regression Models
Ratio regression and capture-recapture - Marco Alfo, Dankmar Bohning and Irene Rocchetti
The Conway-Maxwell-Poisson distribution and capture-recapture count data - Antonello Maruotti and Orasa Anan
The geometric distribution, the ratio plot under the null and the burden of Dengue Fever in Chiang Mai province - Dankmar Bohning and Veerasak Punyapornwithaya
A ratio regression approach to estimate the size of the Salmonella infected flock population using validation information - Carla Azevedo, Dankmar Bohning and Mark Arnold
III Meta-Analysis in Capture–Recapture
On meta-analysis in capture-recapture – John Bunge
A case study on maritime accidents using meta-analysis in capture-recapture – Dankmar Bohning and John Bunge
A meta-analytic generalization of the Lincoln-Petersen-estimator for mark-and-resight studies - Dankmar Bohning, Mehmet Orman, Timur Kose, and John Bunge
IV Extensions of Single Source Models
Estimating the population size via the empirical probability generating function - John Bunge and Sarah Sernaker
Convex estimation - Cecile Durot, Jade Giguelay, Sylvie Huet, Francois Koladjo, and Stephane Robin
Non-parametric estimation of the population size using the empirical probability generating function - Pedro Puig
Extending the truncated Poisson regression model to a time-at-risk model - Maarten J.L.F. Cruyff, Thomas F. Husken, and Peter G.M. van der Heijden
Extensions of the Chao-estimator for covariate information: Poisson case - Alberto Vidal-Diez and Dankmar Bohning
Population size estimation for one-inflated count data based upon the geometric distribution - Panicha Kaskasamkul and Dankmar Bohning
V Multiple Sources
Dual and multiple system estimation: fully observed and incomplete covariates - Peter G.M. van der Heijden, Maarten Cruyff, Joe Whittaker, Bart F.M. Bakker and Paul A. Smith
Population size estimation in CRC Models with continuous covariates - Eugene Zwane
Trimmed dual system estimation - Li-Chun Zhang and John Dunne
Estimation of non-registered usual residents in the Netherlands - Bart F. M. Bakker, Peter G. M. van der Heijden, and Susanna C. Gerritse
VI Latent Variable Models
Population size estimation using a categorical latent variable - Elena Stanghellini and Maria Giovanna Ranalli
Latent class - Rasch models and marginal extensions - Francesco Bartolucci and Antonio Forcina
Performance of hierarchical log-linear models for a heterogeneous population with three lists - Zhiyuan Ma, Chang Xuan Mao, and Yitong Yang
A multidimensional Rasch model for multiple system estimation where the number of lists changes over time - Elvira Pelle, David J. Hessen, and Peter G. M. van der Heijden
Extending the Lincoln-Petersen estimator when both sources are counts - Rattana Lerdsuwansri and Dankmar Bohning
VII Bayesian Approaches
Objective Bayes estimation of the population size using Kemp distributions - Kathryn Barger and John Bunge
Bayesian population size estimation with censored counts - Danilo Alunni Fegatelli, Alessio Farcomeni, and Luca Tardella
VIII Miscellaneous Topics
Uncertainty assessment in capture-recapture studies and the choice of sampling effort - Dankmar Bohning, John Bunge, and Peter G.M. van der Heijden