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This paper presents a novel data-adaptive expert approach to determining the best factor pattern structure in exploratory factor analysis (EFA) models using a clever genetic algorithm (GA) hybridized with information theoretic complexity (ICOMP) criterion as the fitness function. These factor pattern structures from EFA model could then be utilized for various inductive inferences for example to study substantive hypotheses of researchers in the light of the data or could be used asdoi:10.13176/11.335 fatcat:zynbf6rqarft3ka7jobdt4uhme