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Rating scales are used to elicit data about qualitative entities (e.g.,research collaboration). This study presents an innovative method for reducingthe number of rating scale items without the predictability loss. The "areaunder the receiver operator curve method" (AUC ROC) is used. The presentedmethod has reduced the number of rating scale items (variables) to 28.57\%(from 21 to 6) making over 70\% of collected data unnecessary.  Results have been verified by two methods of analysis: Graded Response Model(GRM) and Confirmatory Factor Analysis (CFA). GRM revealed that the new methoddifferentiates observations of high and middle scores. CFA proved that thereliability of the rating scale has not deteriorated by the scale itemreduction. Both statistical analysis evidenced usefulness of the AUC ROCreduction method.

How to reduce the number of rating scale items without predictability loss?