Capture-recapture methods have recently become popular in the social and medical sciences to estimate the size of elusive populations such as illicit drug users or people with a drinking problem. This book brings together important developments which allow the application of these methods with contributions from more than 40 researchers.
Capture-recapture methods have recently become popular in the social and medical sciences to estimate the size of elusive populations such as illicit drug users or people with a drinking problem. This book brings together important developments which allow the application of these methods with contributions from more than 40 researchers.
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.
Inhaltsangabe
I Introductory Part Basic concepts of capture-recapture II 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 flock population using validation information III 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 IV 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-inflated count data based upon the geometric distribution V 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 VI 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 where the number of lists changes over time Extending the Lincoln-Petersen estimator when both sources are counts VII Bayesian Approaches Objective Bayes estimation of the population size using Kemp distributions Bayesian population size estimation with censored counts VIII Miscellaneous Topics Uncertainty assessment in capture-recapture studies and the choice of sampling effort
I Introductory Part Basic concepts of capture-recapture II 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 flock population using validation information III 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 IV 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-inflated count data based upon the geometric distribution V 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 VI 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 where the number of lists changes over time Extending the Lincoln-Petersen estimator when both sources are counts VII Bayesian Approaches Objective Bayes estimation of the population size using Kemp distributions Bayesian population size estimation with censored counts VIII Miscellaneous Topics Uncertainty assessment in capture-recapture studies and the choice of sampling effort
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Shop der buecher.de GmbH & Co. KG Bürgermeister-Wegele-Str. 12, 86167 Augsburg Amtsgericht Augsburg HRA 13309
