Modeling medical data using logistics model
The new technique in data robustness, the least quartile difference (LQD) regression modeling and the widely used model, logit modeling have been studied in analyzing the nonlinear modeling. Research of these nonlinear models covered its discoveries, functions of models, assumption of residuals, pro...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/9592/ |
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| Summary: | The new technique in data robustness, the least quartile difference (LQD) regression modeling and the widely used model, logit modeling have been studied in analyzing the nonlinear modeling. Research of these nonlinear models covered its discoveries, functions of models, assumption of residuals, probability distributions and the estimation techniques. A case study using the two methods of modeling as mentioned above was carried out. The comparison between the least quartile difference (LQD) regression modeling and logit modeling were done to find the better model by using the percentage of accuracy. After comparing the two models, it was found that the least quartile difference (LQD) regression modeling appeared to be the better model, having the highest probability of accuracy and can be proposed as the new effective model. |
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