A log-linear cognitive diagnosis model (LCDM) is estimated via a global optimization approachparticle swarm optimization (PSO), which is an efficient method of handling local maxima problem. The application of the PSO to LCDM estimation is introduced, explicated, and evaluated via a Monte Carlo simulation study in this article. The aim of this paper is to fill the gap between the field of psychometric modeling and machine learning estimation techniques.
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