Results of a Monte Carlo study with 4 populations (3,072 conditions) indicate that when distributions depart markedly from normality, nonparametric analysis and parametric analysis of transformed data show superior power to parametric analysis of raw data. Under conditions studied, parametric analysis of transformed data is more powerful than…

A method is proposed for investigating the intersection of item response functions in the nonparametric item-response-theory model of R. J. Mokken (1971). Results from a Monte Carlo study support the proposed use of the transposed data matrix H(sup T) as an extension to Mokken's approach. (SLD)

Whether it is possible to develop a classification function that identifies the underlying range restriction from sample information alone was investigated in a simulation. Results indicate that such a function is possible. The procedure was found to be relatively accurate, robust, and powerful. (SLD)

Seven univariate procedures for testing omnibus null hypotheses for data gathered from repeated measures designs were evaluated, comparing five alternative approaches with two more traditional procedures. Results suggest that the alternatives are improvements. The most effective alternate procedure in controlling Type I error rates is discussed.…

This article shows how a multivariate approximate degrees of freedom procedure based on the Welch-James procedure as simplified by S. Johansen (1980) can be applied to the analysis of repeated measures designs without assuming covariance homogeneity. A Monte Carlo study illustrates the approach. (SLD)

Proposes a procedure for generating multivariate nonnormal distributions. The procedure, an extension of the Fleishman power method (A. Fleishman, 1978), generates the average value of intercorrelations much closer to population parameters than competing procedures for skewed and heavy tailed distributions and small sample sizes. Reports Monte…

Studied whether moving average or autoregressive moving average models fit two longitudinal data sets previously thought to possess quasi-simplex structures better than the quasi-simplex, one-factor, or autoregressive models. Results of a Monte Carlo study show the importance of evaluating the fit, propriety, and parsimony of models before one…

Extends the basic Markov chain Monte Carlo (MCMC) strategy of R. Patz and B. Junker (1999) for Bayesian inference in complex Item Response Theory settings to address issues such as nonresponse, designed missingness, multiple raters, guessing behaviors, and partial credit (polytomous) test items. Applies the MCMC method to data from the National…

Strategies to avoid the penalties of extra variation described by J. Cornfield and reduced degrees of freedom in community-level trials were compared in Monte Carlo simulations. The three conditions necessary to ensure nominal Type I and Type II error rates are detailed. (SLD)

The authors used a Monte Carlo simulation to examine how the violation of the exchangeability assumption affects empirical Type I error rates of the LMH randomization test (J. R. Levin, L. A. Marascuilo, & L. J. Hubert, 1978). Simulation results showed that the LMH test is not always an appropriate technique for analyzing systematic designs when…

This manuscript introduces a new Bayesian finite mixture methodology for the joint clustering of row and column stimuli/objects associated with two-mode asymmetric proximity, dominance, or profile data. That is, common clusters are derived which partition both the row and column stimuli/objects simultaneously into the same derived set of clusters.…

In this article, a maximum likelihood (ML) approach for analyzing a rather general two-level structural equation model is developed for hierarchically structured data that are very common in educational and/or behavioral research. The proposed two-level model can accommodate nonlinear causal relations among latent variables as well as effects…

We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…

Seven approaches to averaging reliability coefficients are presented. Each approach starts with a unique definition of the concept of "average," and no approach is more correct than the others. Six of the approaches are applicable to internal consistency coefficients. The seventh approach is specific to alternate-forms coefficients. Although the…

In the nineteenth century many people tried to seek a value for the most famous irrational number, [pi], by means of an experiment known as Buffon's needle, consisting of throwing randomly a needle onto a surface ruled with straight parallel lines. Here we propose to extend this experiment in order to evaluate other irrational numbers, such as…