No abstract

Statistics used to estimate the population correlation ratio were reviewed and evaluated. The sampling distributions of Kelley's ε 2 and Hays' ω 2 were studied empirically by computer simulation within the context of a three level one-way fixed effects analysis of variance design. These statistics were found to have rather large standard errors when small samples were used. As with other correlation indices, large samples are recommended for accuracy of estimation.Both & e p s i l o n ; 2 and ω 2 were found to be negligibly biased. Heterogeneity of variances had negligible effects on the estimates under conditions of proportional representativeness of sample sizes with respect to their population counterparts, but combinations of heterogeneity of variance and unrepresentative sample sizes yielded especially poor estimates.EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT 1975, 35, 541-554.

A least squares method is presented for fitting a given matrix A to another given matrix B under choice of an unknown rotation, an unknown translation, and an unknown central dilation. The procedure may be useful to investigators who wish to compare results obtained with nonmetric scaling techniques across samples or who wish to compare such results with those obtained by conventional factor analytic techniques on the same sample.

Thirteen profile similarity measures were compared, using generated data. Profiles were generated from sets of three standards by adding random and normally distributed error components to the profile points of the standards. The three standards within each set were vaned systematically, altering the elevation, scatter, and shape similarities between the standards. A correct classification occurred if the generated profile was most similar to the standard from which it was generated. Significant differences were found between the proportions of correct classifications for the 13 profile similarity measures under all conditions. Osgood and Suci's D and Cattell's rB were superior to or equal to all other measures under all conditions.