Assessing the Quality and Effectiveness of the Factor Score Estimates in Psychometric Factor-Analytic Applications

Abstract

Abstract. This article proposes an approach, intended for factor-analytic (FA) psychometric applications, which aims to assess the extent to which the FA-derived individual score estimates are accurate and allow the respondents to be consistently ordered and effectively differentiated over the range of trait values that is appropriate given the purposes of the test. Three groups of properties are assessed: (a) fineness, (b) probability, and (c) range, and, within each group, different indices are proposed. Overall, the proposal is comprehensive in that it can be used with (a) different factor score estimates derived from both the linear model and the categorical variable methodology model, and (b) any type of unrestricted or restricted FA solution. All the indices proposed have been implemented in a non-commercial and widely known program for exploratory factor analysis. The usefulness of the proposal is illustrated with a real-data example in the personality domain.