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

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
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 04 Apr 2011 08:31
Last Modified: 13 Oct 2017 03:43
URI: http://eprints.ums.edu.my/id/eprint/2680

Actions (login required)

View Item View Item

Browse Repository
Collection
   Articles
   Book
   Speeches
   Thesis
   UMS News
Search
Quick Search

   Latest Repository

Link to other Malaysia University Institutional Repository

Malaysia University Institutional Repository