An Association Rule General Analytic System (ARGAS) for hypothesis testing and data mining applications

2018-11-19T23:27:14Z (GMT) by Rick Parente
The primary purpose of this study was to evaluate the use of an Association Rule General Analytic System (ARGAS) versus the General Linear Model (GLM) for hypothesis testing. Results indicate that the ARGAS provides an better alternative method for testing hypotheses when the assumptions of the GLM are violated. The ARGAS approach can be used with any experimental design to which the GLM can be applied. ARGAS is free of the usual assumptions of the GLM. A second purpose of the study was to illustrate how the ARGAS can be used for hypothesis testing with commonly used experimental designs.