Comparison of regression models in case of non-normality and Heteroscedasticity

Creative Commons License

Kahvecioglu S., YAZICI B.

INTERNATIONAL JOURNAL OF ADVANCED AND APPLIED SCIENCES, vol.3, no.8, pp.18-22, 2016 (ESCI) identifier

  • 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
  • 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.