This study had a two-fold purpose. The first purpose was to compare the rankings of a set of knowledge/skills statements as reported by teachers of students with emotional behavioral disorders and teachers in juvenile correctional special education settings. A survey instrument designed to measure the importance, proficiency, and frequency of use of clusters of knowledge/skills statements was administered to 123 teachers in juvenile correctional special education settings in state institutions. Mann Whitney U analyses were calculated to compare the mean rankings of the two groups of teachers. The findings indicated that teachers in juvenile correctional special education settings and teachers of students with emotional and behavioral disorders were very similar as to which knowledge/skills clusters were important to their job performance, which clusters they were most proficient at using, and which clusters they utilized most frequently. The second purpose was to compare the teachers in juvenile correctional special education settings and to determine whether their mean rankings of the knowledge/skills clusters varied when analyzed by differing categories of age, type of certification held, years of teaching experience, and level of the teachers' education. Analysis of variance revealed no significant difference in the mean rankings in any of the comparison groups. …

Researchers who make predictions from educational data are interested in choosing the best regression model possible. Many criteria have been devised for choosing a full or restricted model, and also for selecting the best subset from an all-possible-subsets regression. The relative practical usefulness of three of the criteria used in selecting a regression model was compared in this study: (a) Mallows' C_p, (b) Amemiya's prediction criterion, and (c) Hagerty and Srinivasan's method involving predictive power. Target correlation matrices with 10,000 cases were simulated so that the matrices had varying degrees of effect sizes. The amount of power for each matrix was calculated after one or two predictors was dropped from the full regression model, for sample sizes ranging from n = 25 to n = 150. Also, the null case, when one predictor was uncorrelated with the other predictors, was considered. In addition, comparisons for regression models selected using C_p and prediction criterion were performed using data from the National Educational Longitudinal Study of 1988.