Estimation of capture probabilities using generalized estimating equations and mixed effects approaches

• Autor(a) principal: Akanda, Md. Abdus Salam
• Data de Publicação: 2014
• Outros Autores: Alpizar-Jara, Russell
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/13755
• topic: Closed population; Generalized linear mixed models; Generalized linear models; Heterogeneity; Population size estimation

Modeling individual heterogeneity in capture probabilities has been one of the most challenging tasks in capture-recapture studies. Heterogeneity in capture probabilities can be modeled as a function of individual covariates, but correlation structure among capture occasions should be taking into account. A proposed generalized estimating equations (GEE) and generalized linear mixed modeling (GLMM) approaches can be used to estimate capture probabilities and population size for capture-recapture closed population models. An example is used for an illustrative application and for comparison with currently used methodology. A simulation study is also conducted to show the performance of the estimation procedures. Our simulation results show that the proposed quasi-likelihood based on GEE approach provides lower SE than partial likelihood based on either generalized linear models (GLM) or GLMM approaches for estimating population size in a closed capture-recapture experiment. Estimator performance is good if a large proportion of individuals are captured. For cases where only a small proportion of individuals are captured, the estimates become unstable, but the GEE approach outperforms the other methods.