Abstract
Existing computer packages for data analysis are not generally sensitive to the underlying assumptions of factor analysis and issues concerning the appropriateness of data. One serious problem in the factor analysis of test items is that of response skew. This paper discusses some strategies for mitigating this problem and emphasizes the use of alternatives to the Pearson-Bravais inter-item correlation coefficient. In particular, it is shown that the Holley-Guilford G-index of association may be interpreted logically as a coefficient of correlation between two binary items, dichotomised at the median of their underlying continua, following a point symmetry adjustment. The G-index is a point symmetry adjusted phi-correlation coefficient. It is argued that principal components analysis of the inter-item matrix of G-indices is less distorted than that of phi-coefficients where parametric assumptions are in doubt.
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