This study involved an investigation of the use of Pearson r, tetrachoric r, phi, phi/phi maximum, and Kendall Tau-B coefficients as measures of association for the incomplete principal components analysis of simulated Likert scale attitudinal data, based on a known factor pattern and possessing different types of severe departures from normality. The results suggested that in addition to being based on few assumptions, Tau-B was most robust, with respect to distributional distortion, with large or small samples, and this coefficient was followed by the Pearson r. The measures based on 2 x 2 tables--tetrachoric r, phi, and phi/phi maximum--tended to be less robust and were seen to be adversely affected by uneven marginal splits, a condition generally present with Likert scale data. (Author)