DIMPACK Version 1.0 for assessing test dimensionality based on a nonparametric conditional covariance approach is reviewed. This software was originally distributed by Assessment Systems Corporation and now can be freely accessed online. The software consists of Windows-based interfaces of three components: DIMTEST, DETECT, and CCPROX/HAC, which…

This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…

Two experiments examined children's metacognitive monitoring of recognition judgments within an eyewitness identification paradigm. A confidence-accuracy (CA) calibration approach was used to examine patterns of calibration, over-/underconfidence, and resolution. In Experiment 1, children (n=619, mean age=11 years 10 months) and adults (n=600)…

DIMTEST is a nonparametric hypothesis-testing procedure designed to test the assumptions of a unidimensional and locally independent item response theory model. Several previous Monte Carlo studies have found that using linear factor analysis to select the assessment subtest for DIMTEST results in a moderate to severe loss of power when the exam…

Discusses problems in detecting nonlinear associations and investigates the use of two statistics for this purpose. Simulation results suggest that the Cramer-von Mises form of the test statistic is generally better than the Kolmogorov-Smirnov form. Discusses the power of this method. (SLD)

Multiple comparison procedures for controlling familywise Type I error and the false discovery rate are described and compared, including the traditional Bonferroni correction, a sequential (step-up) Bonferroni procedure (Hochberg, 1988), and a sequential false discovery rate procedure proposed by Benjamini and Hochberg (1995). Motivation for…

The use of finite intersection tests (FIT) to unify methods for simultaneous inference and to test orthogonal contrasts is discussed. Multiple comparison procedures that combine FIT with sequential hypothesis testing are illustrated, and a simulation strategy is presented to generate values needed for FIT methods. (SLD)

A Monte Carlo simulation examined the Type I error rates and power of four tests of the null hypothesis that a correlation matrix equals the identity matrix. The procedure of C. J. Brien and others (1984) was found to be the most powerful test maintaining stable empirical alpha values. (SLD)

Describes the implementation of a standard Pearson chi-square statistic to test the null hypothesis of bivariate normality for latent variables in the Type I censored model. Assesses the behavior of the statistic through simulation and illustrates the statistic through an empirical example. Discusses limitations of the test. (Author/SLD)

The robustness with respect to Type I error and the power of a proposed test statistic in testing the conjoint hypotheses of mean and variability equality were examined in this simulation study. The conjoint test utilizes the maximum p-value from separate tests of equality of means and equality of variability as its p-value to control the Type I…

Two forms, pure-rank and mixed-rank, of a nonparametric, general, linear model-based statistic that can be used to test several hypotheses are presented. A Monte Carlo study was used to investigate the distributional properties of these forms, and their use is discussed. (SLD)

Blanton and Jaccard questioned the 4-test regression method used by Greenwald et al. to test a pure multiplicative theory. The present authors address Blanton and Jaccard's concerns with a combination of simulations and meta-analysis. Simulations show that (a) Blanton and Jaccard's preferred simultaneous regression method has a severe power loss…

In multigroup covariance structure analysis with structured means, the traditional latent selection model is formulated as a special case of phenotypic selection. Illustrations with real and simulated data demonstrate how one can test specific hypotheses concerning selection on latent variables. (SLD)

Type I error rates for the Johansen test were estimated using simulated data for a variety of conditions. Results indicate that Type I error rates for the Johansen test depend heavily on the number of groups and the ratio of the smallest sample size to the number of dependent variables. Sample size guidelines are presented. (SLD)

Two strategies, derived from J. P. Schaffer (1986), were compared as tests of significance for a complete set of planned orthogonal contrasts. The procedures both maintain an experimentwise error rate at or below alpha, but differ in the manner in which they test the contrast with the largest observed difference. One approach proceeds directly to…