Abstract
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
Article Review Status: Published
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