Model selection for four- and higher-dimensional tables
Paper
Paper/Presentation Title | Model selection for four- and higher-dimensional tables |
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Presentation Type | Paper |
Authors | |
Author | Toleman, Mark |
Editors | O'Rourke, P. K. |
Journal or Proceedings Title | Proceedings of the 1982 Workshop on Biometrical Techniques: Some Analytical Methods for the Analysis of Nominal and Ordinal Data |
Number of Pages | 8 |
Year | 1982 |
Conference/Event | 1982 Workshop on Biometrical Techniques |
Event Details | 1982 Workshop on Biometrical Techniques Event Date 21 to end of 23 Apr 1982 Event Location Brisbane, Australia |
Abstract | As the number of dimensions of the contingency table increases so does the number of possible hierarchical log-linear models. For example, for three dimensions there are eight models and for four dimensions there are 113 models (Bishop et al, 1975). Obviously we cannot test the fit of all these models so we need a method of selecting terms to be included in our 'best fit' model. There is no best method for selecting a log-linear model just as there is no best method for variable selection in multiple regression. Three methods of model selection are discussed, each in the context of a single data set. The program GLIM is used throughout to fit models. |
Keywords | GLIM; generalised linear interactive modelling |
ANZSRC Field of Research 2020 | 490502. Biostatistics |
Public Notes | No evidence of copyright restrictions. |
Byline Affiliations | Faculty of Business and Law |
https://research.usq.edu.au/item/9z128/model-selection-for-four-and-higher-dimensional-tables
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