Useful Statistical Methods for Human Factors Research in Software Engineering: A Discussion on Validation with Quantitative Data
This work addresses the need for better validation methods in human factors research for software engineering, but it is incremental as it advocates for adopting existing techniques from other fields.
The paper argues for applying established statistical validation techniques, such as Test-Retest, Cronbach's α, and Exploratory Factor Analysis, to human factors survey research in software engineering to improve reliability and construct validity.
In this paper we describe the usefulness of statistical validation techniques for human factors survey research. We need to investigate a diversity of validity aspects when creating metrics in human factors research, and we argue that the statistical tests used in other fields to get support for reliability and construct validity in surveys, should also be applied to human factors research in software engineering more often. We also show briefly how such methods can be applied (Test-Retest, Cronbach's α, and Exploratory Factor Analysis).