Capture-Recapture Methods for the Social and Medical Sciences: 1st Edition (Hardback) book cover

Capture-Recapture Methods for the Social and Medical Sciences

1st Edition

Edited by Dankmar Bohning, Peter G.M. van der Heijden, John Bunge

Chapman and Hall/CRC

430 pages | 82 B/W Illus.

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Description

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.

Reviews

"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

Table of Contents

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

About the Editors

Dankmar Böhning is Professor of Medical Statistics and Director of the Southampton Statistical Sciences Research Institute at the University of Southampton. His interests are in capture-recapture modelling, meta-analysis and research synthesis as well as mixed modelling.

John Bunge is Professor of Statistics in the Department of Statistical Science of Cornell University. His interests are capture-recapture modelling, microbiome statistics, and nonclassical probability distribution theory.

Peter. G.M. van der Heijden is Professor of Social Statistics at the University of Utrecht and at the University of Southampton. His interests are capture-recapture modelling for the Social Sciences and Official Statistics.

About the Series

Chapman & Hall/CRC Interdisciplinary Statistics

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Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General
MED105000
MEDICAL / Psychiatry / General