NONMETRIC MULTIDIMENSIONAL ITEM ANALYSIS IN THE CONSTRUCTION OF AN ANXIETY ATTITUDE SURVEY

The present study addresses some of the problems of traditional item analysis during the construction of attitude instruments by using a convergent analysis of three metric and nonmetric multivariate techniques for item analysis. Employing data from a recent administration of a science anxiety questionnaire, the use of maximum likelihood factor analysis followed by oblique rotations, multidimensional scaling, and hierarchical cluster analysis is shown. A high reliable instrument with equally reliable subscales is developed in the process. The reliability of the instrument and its subscales lie between .88 and .92.