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Analysis of Capture-Recapture Data

By Rachel S. McCrea, Byron J. T. Morgan

Chapman and Hall/CRC – 2014 – 328 pages

Series: Chapman & Hall/CRC Interdisciplinary Statistics

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Description

Written for researchers and graduate students in statistics, demography, and the social sciences, this reference provides an overview of capture-recapture—the statistical methods used to estimate population size. It covers model development and examines the technicalities of model diagnostics, an often overlooked aspect in practice. The authors provide examples to demonstrate the statistical nuances that are encountered with complex modeling. They use real-world data sets throughout the text and include stand-alone software programs, such as R and WinBUGS. Chapters contain exercises to assist with reader assimilation of the material.

Contents

Introduction

History of Statistical Ecology; what's wrong with life-tables; connections with human demography and survival analysis. The capture-recapture revolution

Time-line showing the models/developments included in the book

Introduction to computational aspects and software

Introduction to data sets being used

Study design

Estimating Abundance

Schnabel census; importance of assumptions made

Jolly-Seber models

Medical and social applications

Use of computer program estimateN, within R

Survival Estimation - developed in terms of sufficient statistics where possible

Recapture & recovery Models; Cormack-Jolly-Seber model

Multi-state models (explicit modeling of joint recapture-recovery data in terms of a multi-state model)

Multi-event models

Stop-over models

Spatially explicit capture-recapture

Movement and dispersal

Use of computer programs RMARK and R-package SEeR (spatially explicit capturerecapture)

Covariates

Time-varying covariates; genetic effects

Local (spatial) covariates

Individual covariates and dealing with missing values

Model Diagnostics

Model discrimination

Use of Information Criteria

Stepwise score tests; use of computer packages Eagle and MUSE

Use 6fthe Lasso

Goodness-of-fit

Relative versus Absolute

Partitioning of goodness-of-fit; trap-dependence

Sufficient Statistics for absolute goodness-of-fit

Parameter Redundancy; testing using Maple

Combining Information

Fecundity models

Independent information

State-space models; use of Kalman Filter; relationship to capture-recapture. Use of computer package Kalm

Bayesian Approaches

Basic methods; MCMC, Metropolis Hastings, Win BUGS, R2WinBUGS, p-values, model-averaging (and associated dangers)

Model choice (model probabilities and RJMCMC)

Random effects, and their use for analyzing spatial and multi-species data

Presence models

Relationship to survival analysis

Complex developments, including spatial, multi-species and multi-state

Complex Case Studies

Cormorants (multi-state modeling, model selection, goodness of fit)

Newts (stopover modeling, multi-state model, combining information)

Brent Geese (model selection, integrated modeling, covariates)

Sheep/Deer (complex density dependence, life-history strategies, senescence and age-structures; from phenotype to genotype; emigration)

Appendix I: Computational methods

Appendix II: Data

References

Solutions to exercises

Author Bio

Byron J.T. Morgan is a professor of applied statistics in the School of Mathematics, Statistics, and Actuarial Science at the University of Kent.

Rachel S. McCrea is a research associate for the National Centre for Statistical Ecology at the University of Kent.

Name: Analysis of Capture-Recapture Data (Hardback)Chapman and Hall/CRC 
Description: By Rachel S. McCrea, Byron J. T. Morgan. Written for researchers and graduate students in statistics, demography, and the social sciences, this reference provides an overview of capture-recapture—the statistical methods used to estimate population size. It covers model development and...
Categories: Statistical Theory & Methods, Statistics for the Biological Sciences, Biodiversity