The internal correlation--a measure of dependency in a set of variables--is discussed and generalized. Applications of the internal correlation coefficient and its generalizations are given for several data-analytic situations. The internal correlation is illustrated and the concept is expanded to a series of additional indices. (TJH)

Use of internal correlation for statistical analysis--proposed by G. W. Joe and J. L. Mendoza (1989)--is discussed. Focus is on the "content" question (what this application can do with the information that statistics contain) and the "eloquence" question (the advantages of this means of encoding information over other means). (TJH)

Multivariate distributions are studied in which all bivariate regressions can be linearized by separate transformation of each of the variables. A two-stage procedure, first scaling the variables optimally and then fitting a simultaneous equations model, is studied in detail. (SLD)

A two-step procedure is developed for the analysis of pretest-posttest data. Nonlinear canonical correlation analysis is followed by covariance analysis of optimally scaled pretest and posttest measures. The procedure is available in the computer program CANALS. Advantages of the two-step procedure are discussed. (SLD)

Kendall's Tau is often considered equivalent to Spearman's Rho as an ordinal measure of correlation in spite of its different metric. Formulas for converting Tau to Rho are reviewed; and a table of corresponding values is presented for Tau, Rho, and several related indices. (SLD)

The implications of serially correlated effects on the results of generalizability analyses are discussed. Simulated data are provided that demonstrate the biases that serially correlated effects introduce into the results. Serial correlation in measurement effects can have a marked influence on the impression of the dependability of measurement…

A modified "F" test is derived that includes a correction for nonindependence of between-groups and within-groups sample values in analysis of variance (ANOVA) designs. Computer simulations based on normal and nonnormal distributions illustrate the usefulness of the approach, which was more powerful than conventional within-subjects…

Longitudinal studies of personality traits and intelligence have used an exponential function to relate magnitudes of correlations between occasions to the time interval. This exponential function is shown to be equivalent to a quasisimplex model of a stationary process with constant reliability. (SLD)

A reparameterization is formulated that yields estimates of scale-invariant parameters in recursive path models with latent variables, and (asymptotically) correct standard errors, without the use of constrained optimization. The method is based on the logical structure of the reticular action model. (Author)

The insightful discussions by Raudenbush, Rubin, Stuart and Zanutto (RSZ) and Reckase identify important challenges for interpreting the output of VAM and for its use with test-based accountability. As these authors note, VAM are statistical models for the correlations among scores from students who share common teachers or schools during the…

Methods of probability modeling to analyze rater agreement are described, emphasizing their basic similarities and viewing them as variants of a common methodology. Statistical techniques for analyzing agreement data are described to address questions such as how many opinions are required to make a medical diagnosis with necessary accuracy. Kappa…

The estimation of mean and standard errors of the eigenvalues and category quantifications in generalized non-linear canonical correlation analysis (OVERALS) is discussed. Starting points are the delta method equations. The jackknife and bootstrap methods are compared for providing finite difference approximations to the derivatives. Examining the…

A review of cross-validation shrinkage formulas is presented which focuses on the theoretical and practical problems in the use of various formulas. Practical guidelines for use of both formulas and empirical cross-validation are provided. A comparison of results using these formulas in a range of situations is then presented. The result of these…

Three separate papers are included in this report. The first describes a two-stage procedure for choosing from among several instructional programs the one which maximizes the probability of passing the test. The second gives the exact sample sizes required to determine whether a squared multiple correlation coefficient is above or below a known…

One aspect of multiple regression--the shrinkage of the multiple correlation coefficient on cross-validation is reviewed. The paper consists of four sections. In section one, the distinction between a fixed and a random multiple regression model is made explicit. In section two, the cross-validation paradigm and an explanation for the occurrence…