Analysis of Capture-Recapture Data
By Byron J. T. Morgan, Rachel S. McCrea
To Be Published April 15th 2014 by Chapman and Hall/CRC – 256 pages
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 Byron J. T. Morgan, Rachel S. McCrea. 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