A1 Journal article (refereed)
Cautionary note on the two-step transformation to normality (2020)


Rönkkö, M., & Aguirre-Urreta, M. (2020). Cautionary note on the two-step transformation to normality. Journal of Information Systems, 34 (1), 151-166. doi:10.2308/isys-52255


JYU authors or editors


Publication details

All authors or editors: Rönkkö, Mikko; Aguirre-Urreta, Miguel

Journal or series: Journal of Information Systems

ISSN: 0888-7985

eISSN: 1558-7959

Publication year: 2020

Volume: 34

Issue number: 1

Pages range: 151-166

Publisher: American Accounting Association

Publication country: United States

Publication language: English

DOI: http://doi.org/10.2308/isys-52255

Open Access: Publication channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/68924


Abstract

Templeton and Burney (2017) proposed a two-step normality transformation as a remedy for non-normally distributed data, which are commonly found in AIS research. We argue that, rather than transforming the data toward normality, researchers should first seek to analyze and understand the sources of non-normality. Using simulated datasets, we demonstrate three sources of non-normality and their consequences for regression estimation. We then demonstrate that the two-step transformation cannot solve any of these problems and that each source of non-normality can be handled with alternative, existing techniques. We further present two empirical examples to demonstrate these issues with real datasets.


Keywords: normal distribution; regression analysis

Free keywords: two-step transformation


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2020

Preliminary JUFO rating: 1


Last updated on 2020-09-07 at 23:11