An Association Rule General Analytic System (ARGAS) for hypothesis testing in qualitative and quantitative research (Published)
This paper describes an Association Rule General Analytic System (ARGAS) as an alternative to the General Linear Model (GLM) for hypothesis testing. We illustrate how the ARGAS can be used to analyze both qualitative and quantitative research data. The advantages of the ARGAS approach derives from the fact that it is designed to analyze words or numbers that are converted into words. Unlike the GLM, it does not have any distributional assumptions. Association rule calculations are well-developed and there are a variety of computer software applications available that expedite the computations. The purpose of this study is to illustrate how the ARGAS can be applied and how to interpret the results.
Keywords: ARGAS, GLM, Pattern Recognition, association rule analysis, hypothesis testing, qualitative, quantitative
An Association Rule General Analytic System (ARGAS) for hypothesis testing in qualitative and quantitative research (Published)
This paper describes an Association Rule General Analytic System (ARGAS) as an alternative to the General Linear Model (GLM) for hypothesis testing. We illustrate how the ARGAS can be used to analyze both qualitative and quantitative research data. The advantages of the ARGAS approach derives from the fact that it is designed to analyze words or numbers that are converted into words. Unlike the GLM, it does not have any distributional assumptions. Association rule calculations are well-developed and there are a variety of computer software applications available that expedite the computations. The purpose of this study is to illustrate how the ARGAS can be applied and how to interpret the results.
Keywords: ARGAS, GLM, Pattern Recognition, association rule analysis, hypothesis testing, qualitative, quantitative
Reflecting on the Debates and Action of Mixed Methods Adoption in Business Research: Why Postgraduate Researchers Should Start Thinking This Way (Published)
The purpose of this paper is to evaluate the philosophical arguments underpinning the choice of mixed method [MM] research design. However, the study concluded that mixing research methods in business research is important as it helps to strengthen findings and recommendations arising from a given research study. More so, we recommend for postgraduate researchers to rationalise their choice of mixing methods based on complementarities, research priority, purpose and the implementation of findings and not on the basis of philosophical ontology and epistemology. This has been found to be the reason underpinning the much-lauded arguments in the adoption of mix methods
Keywords: Concurrent, Mixed Methods, Sequential, qualitative, quantitative