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- Title
Using imputation and mixture model approaches to integrate multi-state capture-recapture models with assignment information.
- Authors
Wen, Zhi; Pollock, Kenneth H.; Nichols, James D.; Waser, Peter M.; Cao, Weihua
- Abstract
In this article, we first extend the superpopulation capture-recapture model to multiple states (locations or populations) for two age groups., Wen et al., (2011; 2013) developed a new approach combining capture-recapture data with population assignment information to estimate the relative contributions of in situ births and immigrants to the growth of a single study population. Here, we first generalize Wen et al., (2011; 2013) approach to a system composed of multiple study populations (multi-state) with two age groups, where an imputation approach is employed to account for the uncertainty inherent in the population assignment information. Then we develop a different, individual-level mixture model approach to integrate the individual-level population assignment information with the capture-recapture data. Our simulation and real data analyses show that the fusion of population assignment information with capture-recapture data allows us to estimate the origination-specific recruitment of new animals to the system and the dispersal process between populations within the system. Compared to a standard capture-recapture model, our new models improve the estimation of demographic parameters, including survival probability, origination-specific entry probability, and especially the probability of movement between populations, yielding higher accuracy and precision.
- Subjects
MULTIPLE imputation (Statistics); DATA analysis; RECAPTURE rules; MARK &; recapture (Population biology); PROBABILITY theory; KANGAROO rats
- Publication
Biometrics, 2014, Vol 70, Issue 2, p323
- ISSN
0006-341X
- Publication type
Article
- DOI
10.1111/biom.12155