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| Trenkel, Verena. |
| A simple two-stage biomass random effects population dynamics model is presented for carrying out fish stock assessments based on survey indices using no commercial catch information. Recruitment and biomass growth are modelled as random effects, reducing the number of model parameters while maintaining model flexibility. No assumptions regarding natural mortality rates are required. The performance of the method was evaluated using simulated data with emphasis on identifying parameter redundancy, which showed that the variance of the biomass growth random effect might only be estimable if large (> 0.2). The full and two nested models were fitted to European anchovy (Engraulis encrasicolus) in the Bay of Biscay using two survey series. The best-fitting... |
| Tipo: Text |
Palavras-chave: Survey based assessment; Population state; Random effects. |
| Ano: 2008 |
URL: http://archimer.ifremer.fr/doc/2008/publication-4565.pdf |
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| Gutierrez, Roberto G.. |
| Frailty models are the survival data analog to regression models, which account for heterogeneity and random effects. A frailty is a latent multiplicative effect on the hazard function and is assumed to have unit mean and variance θ, which is estimated along with the other model parameters. A frailty model is an heterogeneity model where the frailties are assumed to be individual- or spell-specific. A shared frailty model is a random effects model where the frailties are common (or shared) among groups of individuals or spells and are randomly distributed across groups. Parametric frailty models were made available in Stata with the release of Stata 7, while parametric shared frailty models were made available in a recent series of updates. This article... |
| Tipo: Journal Article |
Palavras-chave: Parametric survival analysis; Frailty; Random effects; Overdispersion; Heterogeneity; Research Methods/ Statistical Methods. |
| Ano: 2002 |
URL: http://purl.umn.edu/115948 |
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