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Estimated Time One year Two years Do not know Five years Three years Upgrading is ongoing Do not answer Number of Companies 25 11 7 5 4 2 2 Percentage of Companies 15.9% 7.0% 4.5% 3.2% 2.5% 1.3% 1.3% Table 14. Estimated time to upgrade kilns. 4.1.10. Logistic Regression A model was developed to provide a better understanding of key kiln drying problems and issues that affected a company's decision to upgrade its kilns. The model was used for exploratory purposes rather than making predictions. Since the values of the coefficients for the various variables in the model are affected by the specific variables entered into the model, it is not advisable to use the model for predictive purposes. The outcome is determined by the scores for the variables in questions about: a) capacity of largest kiln, b) dried product quality, c) drying process, d) kiln control, and e) kiln drying related knowledge of groups. Other combinations of variables were also examined. However, the above combination produced the model with the highest values for the Cox and Snell R 2 and Nagelkerke R 2 . These two R 2 measures assess the strength of association for a model. They are used to compare models between them. Cox and Snell R2 is based on log-likelihoods, considers sample size, and cannot take a maximum value of one. Nagelkerke R2 can reach a maximum value of one (Tabachnick & Fidell, 2001). For this model, Cox & Snell R 2 had a value of 0.231 and Nagelkerke R 2 had a value of 0.319. The method used was Backward: Conditional. Backward methods begin with a model containing all independent variables and then test if removing one such variable will affect significantly the fit of the model to the data. This method was chosen instead of the Enter method because no theory testing or 55PDF Image | KILN DRYING PROBLEMS AND ISSUES IN CANADA
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