Maximum Likelihood Factor Analysis of Attitude Data

Abstract

Maximum likelihood factor analysis is a useful technique for analyzing attitude data. The solution can be tested statistically for goodness of fit. Companion procedures for restricting the factor solution permit the testing of hypothesized factor structures. Thus the technique can be used to construct solutions that are more clearly interpretable while still providing adequate fit to the data. A case example is given to illustrate the use of the technique.