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

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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
Uncontrolled Keywords:Asthma, Best model, Eight selection criteria, Interaction, Model selection, Multiple regression
Subjects:?? RC581-607 ??
Divisions:SCHOOL > School of Science and Technology
ID Code:2680
Deposited By:IR Admin
Deposited On:04 Apr 2011 16:31
Last Modified:20 Sep 2016 15:45

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