Multiple linear regressional in forecasting the number of asthmatics

Darmesah Gabda and Zainodin Hj. Jubok and Kamsia Budin and Suriani Hassan (2008) Multiple linear regressional in forecasting the number of asthmatics. WSEAS Transactions on Information Science and Applications, 5 (6). pp. 972-977. ISSN 1790-0832

[img]
Preview
Text
Multiple_linear_regressional_in_forecasting_the_number_of_asthmatics.pdf

Download (123kB) | Preview
[img] Text
Multiple linear regressional in forecasting the number of asthmatics.pdf
Restricted to Registered users only

Download (434kB)

Abstract

The objective of this study was to determine the association between the number of asthmatic patients in Kota Kinabalu, Sabah with the air quality and meteorological factors using multiple linear regression. Four significant correlation coefficient variables were considered in the multiple linear regression. There were 32 possible models considered together with the related interaction variables and the best model was obtained using the eight selection criteria (8SC). The result showed that the best model obtained could represent the cause of the rise in the number of asthmatics.

Item Type: Article
Keyword: Asthma, Best model, Eight selection criteria, Interaction, Model selection, Multiple regression
Subjects: R Medicine > RC Internal medicine > RC31-1245 Internal medicine > RC581-951 Specialties of internal medicine > RC581-607 Immunologic diseases. Allergy
Department: SCHOOL > School of Science and Technology
Depositing User: ADMIN ADMIN
Date Deposited: 04 Apr 2011 16:31
Last Modified: 29 Sep 2021 08:36
URI: https://eprints.ums.edu.my/id/eprint/2680

Actions (login required)

View Item View Item