Journal of Agricultural, Biological, and Environmental Statistics

, Volume 16, Issue 2, pp 253–268

Full Open Population Capture–Recapture Models With Individual Covariates


DOI: 10.1007/s13253-010-0052-4

Cite this article as:
Schofield, M.R. & Barker, R.J. JABES (2011) 16: 253. doi:10.1007/s13253-010-0052-4


Traditional analyses of capture–recapture data are based on likelihood functions that explicitly integrate out all missing data. We use a complete data likelihood (CDL) to show how a wide range of capture–recapture models can be easily fitted using readily available software JAGS/BUGS even when there are individual-specific time-varying covariates. The models we describe extend those that condition on first capture to include abundance parameters, or parameters related to abundance, such as population size, birth rates or lifetime. The use of a CDL means that any missing data, including uncertain individual covariates, can be included in models without the need for customized likelihood functions. This approach also facilitates modeling processes of demographic interest rather than the complexities caused by non-ignorable missing data. We illustrate using two examples, (i) open population modeling in the presence of a censored time-varying individual covariate in a full robust design, and (ii) full open population multi-state modeling in the presence of a partially observed categorical variable. Supplemental materials for this article are available online.

Key Words

Capture–recaptureDemographic parametersHierarchical modelingIndividual covariatesJAGS/BUGS

Supplementary material

13253_2010_52_MOESM1_ESM.pdf (75 kb)
(PDF 75.1 KB)

Copyright information

© International Biometric Society 2011

Authors and Affiliations

  1. 1.Department of StatisticsColumbia UniversityNew YorkUSA
  2. 2.Department of StatisticsUniversity of KentuckyLexingtonUSA
  3. 3.Department of Mathematics and StatisticsUniversity of OtagoDunedinNew Zealand