Comparison of regression models in case of non-normality and Heteroscedasticity
INTERNATIONAL JOURNAL OF ADVANCED AND APPLIED SCIENCES, vol.3, no.8, pp.18-22, 2016 (ESCI)
- Publication Type: Article / Article
- Volume: 3 Issue: 8
- Publication Date: 2016
- Doi Number: 10.21833/ijaas.2016.08.004
- Journal Name: INTERNATIONAL JOURNAL OF ADVANCED AND APPLIED SCIENCES
- Journal Indexes: Emerging Sources Citation Index (ESCI)
- Page Numbers: pp.18-22
- Keywords: Generalized p values, Generalized p values in regression, Regression analysis in case of Assumption violation, Comparison of regression coefficients
- Open Archive Collection: AVESIS Open Access Collection
- Anadolu University Affiliated: Yes
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. (C) 2016 The Authors. Published by IASE.