
	Trends in Applied Sciences Research
	Year: 2011 \| Volume: 6 \| Issue: 11 \| Page No.: 1241-1255 DOI: 10.3923/tasr.2011.1241.1255

An Alternative Multicollinearity Approach in Solving Multiple Regression Problem

H.J. Zainodin, A. Noraini and S.J. Yap

Abstract: This study illustrated the procedures in selecting the best model when there are more than one independent variables. In this case, multiple regressions were used to analyze the data. First of all, all of the possible models are listed out. Then, in order to obtain the selected models, the multicollinearity test and coefficient test were carried out on all of the possible models. In this study, the alternative method was used to overcome multicollinearity, rather than the conventional method. After that, the best model was obtained by using the Eight Selection Criteria (8SC). Meanwhile, the normality test and randomness test were also carried out on the residuals of the best model. As a result, by getting the best model, the main factor that indicated the changes of percentage of body fat in men can be identified.

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How to cite this article:

H.J. Zainodin, A. Noraini and S.J. Yap, 2011. An Alternative Multicollinearity Approach in Solving Multiple Regression Problem. Trends in Applied Sciences Research, 6: 1241-1255.

DOI: 10.3923/tasr.2011.1241.1255

URL: https://scialert.net/abstract/?doi=tasr.2011.1241.1255

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