A generalized estimating equations approach for analysis of the impact of new technology on a trawl fishery
Bishop, J., Die, D., & Wang, Y-G. (2000) A generalized estimating equations approach for analysis of the impact of new technology on a trawl fishery. Australian & New Zealand Journal of Statistics, 42(2), pp. 159-177.
The article describes a generalized estimating equations approach that was used to investigate the impact of technology on vessel performance in a trawl fishery during 1988-96, while accounting for spatial and temporal correlations in the catch-effort data. Robust estimation of parameters in the presence of several levels of clustering depended more on the choice of cluster definition than on the choice of correlation structure within the cluster. Models with smaller cluster sizes produced stable results, while models with larger cluster sizes, that may have had complex within-cluster correlation structures and that had within-cluster covariates, produced estimates sensitive to the correlation structure. The preferred model arising from this dataset assumed that catches from a vessel were correlated in the same years and the same areas, but independent in different years and areas. The model that assumed catches from a vessel were correlated in all years and areas, equivalent to a random effects term for vessel, produced spurious results. This was an unexpected finding that highlighted the need to adopt a systematic strategy for modelling. The article proposes a modelling strategy of selecting the best cluster definition first, and the working correlation structure (within clusters) second. The article discusses the selection and interpretation of the model in the light of background knowledge of the data and utility of the model, and the potential for this modelling approach to apply in similar statistical situations.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Journal Article|
|Additional Information:||ISI Document Delivery No.: 322MQ
Times Cited: 23
Cited Reference Count: 23
Bishop, J Die, D Wang, YG
Blackwell publ ltd
|Keywords:||covariance, fishing power, generalized estimating equations, overdispersion, Poisson, spatial and temporal correlations, longitudinal data-analysis, northern-prawn-fishery, linear-models, binary data, regression, australia|
|Divisions:||Current > QUT Faculties and Divisions > Science & Engineering Faculty|
|Copyright Owner:||Copyright Australian Statistical Publishing Association Inc. 2000|
|Deposited On:||20 Nov 2015 04:15|
|Last Modified:||20 Nov 2015 04:15|
Repository Staff Only: item control page