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Title: | On the use of corrections for overdispersion | Authors: | LINDSEY, James | Issue Date: | 1999 | Publisher: | BLACKWELL PUBL LTD | Source: | JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 48. p. 553-561 | Abstract: | In studying fluctuations in the size of a blackgrouse (Tetrao tetrix) population, an autoregressive model using climatic conditions appears to follow the changes quite well. However, the deviance of the model is considerably larger than its number of degrees of freedom. A widely used statistical rule of thumb holds that overdispersion is present in such situations, but model selection based on a direct likelihood approach can produce opposing results. Two further examples, of binomial and of Poisson data, have models with deviances that are almost twice the degrees of freedom and yet various overdispersion models do not fit better than the standard model for independent data. This can arise because the rule of thumb only considers a point estimate of dispersion, without regard for any measure of its precision. A reasonable criterion for detecting overdispersion is that the deviance be at least twice the number of degrees of freedom, the familiar Akaike information criterion, but the actual presence of overdispersion should then be checked by some appropriate modelling procedure. | Notes: | Limburgs Univ Ctr, Dept Biostat, B-3590 Diepenbeek, Belgium.Lindsey, JK, Limburgs Univ Ctr, Dept Biostat, Univ Campus, B-3590 Diepenbeek, Belgium. | Keywords: | Akaike information criterion; beta-binomial distribution; direct likelihood inference; negative binomial distribution; overdispersion | Document URI: | http://hdl.handle.net/1942/3001 | ISI #: | 000083762200009 | Type: | Journal Contribution | Validations: | ecoom 2000 |
Appears in Collections: | Research publications |
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