A new formula, expressing relative efficiency solely in terms of the standard errors of measurement and the frequency of distributions of true scores, is developed for the relative efficiency of two tests measuring the same trait. Subtests from the Scholastic Aptitude Test provide a numerical illustration. (Author/RC)

In analyzing exploratory repeated measures data with more than two measures, two competing tests must be administered simultaneously if one is to make an efficient and effective decision regarding the tenability of the null hypothesis of no differences among measurement means. Obviously, such a procedure is not without a cost vis-a-vis Type I…

This Digest presents a discussion of the assumptions of multiple regression that is tailored to the practicing researcher. The focus is on the assumptions of multiple regression that are not robust to violation, and that researchers can deal with if violated. Assumptions of normality, linearity, reliability of measurement, and homoscedasticity are…

The relationship between generalizability and validity is explained, making four important points. The first is that generalizability coefficients provide upper bounds on validity. The second point is that generalization is one step in most interpretive arguments, and therefore, generalizability is a necessary condition for the validity of these…

Asymptotic distribution theory of Brogden's form of biserial correlation coefficient is derived and large sample estimates of its standard error obtained. Its relative efficiency to the biserial correlation coefficient is examined. Recommendations for choice of estimator of biserial correlation are presented. (Author/JKS)

Corrections for restriction in range due to explicit selection assume linearity of regression and homoscedastic array variances. A Monte Carlo study was conducted to examine the effects of some common forms of violation of these assumptions. (Author/CP)

Two studies, both using Type 12 sampling, are presented in which the effects of violating the assumption of essential parallelism in setting confidence intervals are studied. Results indicate that as long as data manifest properties of essential parallelism, the two methods studied maintain precise Type I error control. (SLD)

Monte Carlo study results show that recently proposed multiple comparison procedures (MCPs) that are not intended to control the familywise error rate had consistently larger true model rates than did familywise error controlling MCPs. (SLD)

Used Monte Carlo methods to examine the Type I error rates for randomization tests applied to single-case data arising from ABAB designs involving random, systematic, or response-guided assignment of interventions. Discusses conditions under which Type I error rate is controlled or is not. (SLD)

Conducted a reliability generalization study of Kolb's Learning Style Inventory (LSI; D. Kolb, 1976). Results for 34 studies indicate that internal consistency and test-retest reliabilities for LSI scores fluctuate considerably and contribute to deleterious cumulative measurement error. (SLD)

Type I error rates and statistical power for the univariate F test and the James second-order test were estimated for the two-factor fixed-effects completely randomized design. Results reveal that the F test Type I error rate can exceed the nominal significance level when cell variances differ. (SLD)

Studied three procedures for estimating the standard errors of school passing rates using a generalizability theory model and considered the effects of student sample size. Results show that procedures differ in terms of assumptions about the populations from which students were sampled, and student sample size was found to have a large effect on…

Reference-reliability relates variability due to change and error. It indicates whether some suspected change can be reliably differentiated from random fluctuations. A means by which the process of change can be measured at different points in time is outlined, using empirical data. (TJH)