Methods and indices based on item response theory (IRT) for detecting and diagnosing aberrant response patterns are reviewed. These indices are divided into three groups: (1) residuals-based; (2) likelihood-based; and (3) ratio of covariances-based (extended cautions). For each index, the determination of its sampling distribution as well as its…

This simple method for simulating the Central Limit Theorem with students in a beginning nonmajor statistics class requires students to use dice to simulate drawing samples from a discrete uniform distribution. On a chalkboard, the distribution of sample means is superimposed on a graph of the discrete uniform distribution to provide visual…

A major problem in the research concerning distributional and other properties of reliability coefficients has been the non-existence or inaccessibility of adequate test data for use in empirical verification of hypothetical conclusions. The purpose of this paper is to develop a technique for the simulation of test item scores through the use of…

A computer-based learning simulation was developed at Florida State University which allows for high interactive responding via a time-sharing terminal for the purpose of demonstrating descriptive and inferential statistics. The statistical simulation (STATSIM) is comprised of four modules--chi square, t, z, and F distribution--and elucidates the…

A Statistical Experiment Simulator (STEXSIM) has been developed which permits one to stimulate on a digital computer a wide range of experimental environments. As a teaching aid in applied statistics, it provides a means for an instructor to define a completely crossed factorial model with up to seven fixed or random main effects, three two-factor…

Describes a simulation method for measurement of errors that requires calculators and tables of random digits. Each student simulates the random behaviour of the component variables in the function and by combining the results of all students, the outline of the sampling distribution of the function can be obtained. (GA)

Two new indices to detect answer copying on a multiple-choice test, S(1) and S(2) (subscripts), are proposed. The S(1) index is similar to the K-index (P. Holland, 1996) and the K-overscore(2), (K2) index (L. Sotaridona and R. Meijer, in press), but the distribution of the number of matching incorrect answers of the source (examinee s) and the…

This paper aims to describe a Bayesian approach to modeling and estimating cognitive models both in terms of statistical machinery and actual instrument development. Such a method taps the knowledge of experts to provide initial estimates for the probabilistic relationships among the variables in a multivariate latent variable model and refines…

A Monte Carlo study of the validity of the Inverse Scree Test under conditions where true group membership is known was conducted. Fifty cluster analyses of each distribution involving 2 to 5 true groups of 3,000 simulated subjects were made. Implications for the data analyst are discussed. (SLD)

Procedures for implementing parallel analysis (PA) criteria in practice were compared, examining regression equation methods that can be used to estimate random data eigenvalues from known values of the sample size and number of variables. More internally accurate methods for determining PA criteria are presented. (SLD)

A Monte Carlo study determined the Inverse Scree Test's shape with various numbers of true groups and under different conditions of distribution shape and sample size. Six simulated distributions of 3,000 subjects each and 1 with 1,500 were created. Findings suggest relative distribution independence, number independence, and modest…

Ignoring a level can have a substantial impact on the conclusions of a multilevel analysis. For intercept-only models and for balanced data, we derive these effects analytically. For more complex random intercept models or for unbalanced data, a simulation study is performed. Most important effects concern estimates and corresponding standard…

The regression trunk approach (RTA) is an integration of regression trees and multiple linear regression analysis. In this paper RTA is used to discover treatment covariate interactions, in the regression of one continuous variable on a treatment variable with "multiple" covariates. The performance of RTA is compared to the classical…