ABSTRACT
Factor analysis begins with a data matrix. Each variable in the data matrix has a particular mean, standard deviation, and distribution. Variations in the characteristics of the variables may have a definite effect on a factor analysis. Characteristics of the variables can be altered by both linear and nonlinear transformations. Factor analysis generally begins with a summary of the relationships among the variables, such as a correlation matrix. Factor-analytic procedures are then applied as a convenient and efficient method for finding the factor pattern. The prime differences between the indices of association that might be used for factor-analytic purposes are twofold. On the one hand, they vary in the extent to which the standard procedures for factor analysis. On the other hand, the indices vary in the extent to which they are influenced by different aspects of the data.
