Modeling pattern in collections of parameters
Journal of Wildlife Management
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Abstract
Wildlife management is increasingly guided by analyses of large and complex datasets. The description of such datasets often requires a large number of parameters, among which certain patterns might be discernible. For example, one may consider a long-term study producing estimates of annual survival rates; of interest is the question whether these rates have declined through time. Several statistical methods exist for examining pattern in collections of parameters. Here, I argue for the superiority of 'random effects models' in which parameters are regarded as random variables, with distributions governed by 'hyperparameters' describing the patterns of interest. Unfortunately, implementation of random effects models is sometimes difficult. Ultrastructural models, in which the postulated pattern is built into the parameter structure of the original data analysis, are approximations to random effects models. However, this approximation is not completely satisfactory: failure to account for natural variation among parameters can lead to overstatement of the evidence for pattern among parameters. I describe quasi-likelihood methods that can be used to improve the approximation of random effects models by ultrastructural models.
Suggested Citation
Link, W., 1999, Modeling pattern in collections of parameters: Journal of Wildlife Management, v. 63, no. 3, p. 1017-1027, https://doi.org/10.2307/3802817 •.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Modeling pattern in collections of parameters |
| Series title | Journal of Wildlife Management |
| DOI | 10.2307/3802817 • |
| Volume | 63 |
| Issue | 3 |
| Year Published | 1999 |
| Language | English |
| Publisher | Wildlife Society |
| Contributing office(s) | Patuxent Wildlife Research Center |
| Description | 11 p. |
| First page | 1017 |
| Last page | 1027 |