International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN:2313-626X

Volume 3, Issue 8  (August 2016), Pages:  18-22

Title: Comparison of regression models in case of non‐normality and Heteroscedasticity

Authors:  Seray Kahvecioglu, Berna Yazici *

Affiliations:

Anadolu University, Science Faculty, Department of Statistics, Eskisehir, Turkey

http://dx.doi.org/10.21833/ijaas.2016.08.004

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Abstract:

In regression analysis, in case of comparing two regression models and coefficients where the distribution of variables in question is not known, generalized p values may be used. The generalized p value is an extended version of the classical p value which provides only approximate solutions. Use of approximate methods, generalized p value, has better results, performance with small samples. In this study, the generalized p value – which may be used alternatively when different assumptions aren’t fulfilled - is researched theoretically; a simulation is conducted and an application in regression analysis is given. It is concluded that in generalized p value works well for the comparison of regression coefficients both under non-normality and heteroscedasticity. 

© 2016 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Generalized p values, Generalized p values in regression, Regression analysis in case of Assumption violation, Comparison of regression coefficients

Article History: Received 4 July 2016, Received in revised form 14 August 2016, Accepted 14 August 2016

Digital Object Identifier: http://dx.doi.org/10.21833/ijaas.2016.08.004

Citation:

Kahvecioglu S and Yazici B (2016). Comparison of regression models in case of non‐normality and Heteroscedasticity. International Journal of Advanced and Applied Sciences, 3(8): 18-22

http://www.science-gate.com/IJAAS/V3I8/Kahvecioglu.html

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