Monte Carlo procedures are used to develop stress distributions using Kruskal's second stress formula. These distributions can be used in multidimensional scaling procedures to determine whether a set of data has other than random structure. (Author/JKS)

Four testing procedures for establishing the number of non-zero population roots in canonical analysis are investigated. Results of a Monte Carlo study indicate that three well-established procedures were effective, and a new procedure designed to correct a supposed flaw in the other procedures was ineffective. (JKS)

A general procedure is provided for comparing correlation coefficients between optimal linear composites. It allows computationally efficient significance tests on independent or dependent multiple correlations, partial correlations, and canonical correlations, with or without the assumption of multivariate normality. Evidence from Monte Carlo…

Showed that reliabilities in the .50 range can be obtained when raters rule out only 15-20% of the items on the Position Analysis Questionnaire as "Does Not Apply" and respond randomly to the remainder. (Author/ABB)

In order to make the parallel analysis criterion for determining the number of factors in factor analysis easy to use, regression equations for predicting the logarithms of the latent roots of random correlation matrices, with squared multiple correlations on the diagonal, are presented. (Author/JKS)

A special case of the homogeneity of effect size test, as applied to pairwise comparisons of standardized mean differences, was evaluated. Procedures for comparing pairs of pretest to posttest effect sizes, as well as pairs of treatment versus control group effect sizes, were examined. Monte Carlo simulation was used to generate Type I error rates…

The effect of a nonlinear regression term on the behavior of the standard analysis of covariance (ANCOVA) F test was investigated for balanced and randomized designs through a Monte Carlo study. The results indicate that the use of the standard analysis of covariance model when a quadratic term is present has little effect on Type I error rates…

Research was conducted to provide educational researchers with a choice of pairwise multiple comparison procedures (P-MCPs) to use with single group repeated measures designs. The following were studied through two Monte Carlo (MC) simulations: (1) The T procedure of J. W. Tukey (1953); (2) a modification of Tukey's T (G. Keppel, 1973); (3) the…

Multiple linear regression is used to model the effects of violating statistical assumptions on the likelihood of making a Type I error. This procedure is illustrated for the student's t-test (for independent groups) using data from previous Monte Carlo studies in which the actual alpha levels associated with violations of the normality…

The level of standardized effect sizes obtained by chance and the use of significance tests to guard against spuriously high standardized effect sizes were studied. The concept of the "protected effect size" is also introduced. Monte Carlo methods were used to generate data for the study using random normal deviates as the basis for sample means…

One set of approaches to the problem of clustering with dichotomous data in cluster analysis (CA) was studied. The techniques developed for clustering with binary data involve calculating distances between observations based on the variables and then applying one of the standard CA algorithms to these distances. One of the groups of distances that…

This study explored two methods that are used to assess the dimensionality of item response data. The paper begins with a discussion of the assessment dimensionality and the use of factor-analytic procedures. A number of problems associated with using linear factor analyses to assess dimensionality are also considered. A procedure is presented for…

Describes Monte Carlo simulation studies and their application in vocational education research. Explains study design and analysis as well as use and evaluation of results. (SK)

Describes the development and instructional use of a Microsoft Excel spreadsheet template that facilitates analytical and Monte Carlo risk analysis of investment decisions. Discusses a variety of risk assessment methods followed by applications of the analytical and Monte Carlo methods. Uses a case study to illustrate use of the spreadsheet tool…

Outlines an approach to differential item functioning (DIF) analysis using hierarchical linear regression that makes it possible to combine results of logistic regression analyses across items to identify consistent sources of DIF, to quantify the proportion of explained variation in DIF coefficients, and to compare the predictive accuracy of…