Nonlinear Transformations in Organizational Research: Possible Problems and Potential Solutions
By Thomas E. Becker, Melissa M. Robertson, Robert J. Vandenberg. Organizational Research Methods, 2018
54 citations recorded by the source corpus.
We examined the use of nonlinear transformation of variables in a random sample of 323 articles published in six top journals during 2012-2017. Coding categories included the number of transformed variables, the type of transformation, the kinds of variables transformed, reasons provided for transforming variables, how transformed results were reported, and pre- and posttransformation analysis of variables. Common problems include insufficient justification for transforming variables, overreliance on log transformations, failure to report important information on the effects of transformation, and incomplete reporting and discussion of transformed results. Perhaps most importantly, there was frequent misalignment between statements of hypotheses, typically stated in terms of nontransformed variables, and the transformed data used to test them. We discuss the implications of these problems for science and practice, offer recommendations for addressing the issues, and provide illustrations of how to implement the recommendations.
Subfields: Management Information Systems, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/3034219c3a30f6eda8a6a44191afd2d494590e11
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Information Systems
- Markku V. J. Maula
- E. Aalto
- Miguel I. Aguirre-Urreta
- W. Stam
- Mikko Rönkkö
- Henni Tenhunen
- Marko Sarstedt
- Christian M. Ringle
In Management Science and Operations Research
Citations in the corpus
- Enhancing Rigor in Quantitative Entrepreneurship Research (2019, background): “4 This is problematic because using transformed variables can severely undermine the validity and interpretation of findings (Becker et al., 2018).”
- Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects (2021, background): “These myths may have been caused by the use of transformations without providing supporting citations (Becker et al., 2019).”