The effect that collapsing ordered polytomous variable scales has on structural equation measurement model parameter estimates was examined. Four parameter estimation procedures were investigated in a Monte Carlo study. Collapsing categories in ordered polytomous variables had little effect when latent projection procedures were used. (SLD)

A Monte Carlo study explores the robustness assumption in structural equation modeling of using a full information normal theory generalized least-squares estimation procedure on Type I censored data. The efficacy of the following proposed alternate estimation procedures is assessed: asymptotically distribution free estimator and a latent…

Coefficient alpha was examined through computer simulation as an estimate of test reliability under violation of two assumptions. Coefficient alpha underestimated reliability under violation of the assumption of essential tau-equivalence of subtest scores and overestimated it under violation of the assumption of uncorrelated subtest error scores.…

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)

Type I error rates for PARSCALE's fit statistic were examined. Data were generated to fit the partial credit or graded response model, with test lengths of 10 or 20 items. The ability distribution was simulated to be either normal or uniform. Type I error rates were inflated for the shorter test length and, for the graded-response model, also for…

The present study compares the robustness of two different one way fixed-effects analysis of covariance (ANCOVA) models to investigate whether the model which uses a test statistic incorporating estimates of separate unequal regression slopes is more robust than the conventional model which assumes the slopes are equal. (Author/BW)

Effects of violating the independence assumption when combining correlation coefficients in a meta-analysis were studied. This Monte-Carlo simulation varied sample size, predictor number, population intercorrelation among predictors, and population correlation between predictors and criterion. Combining statistics from nonindependent data in a…

This study reports results of an investigation based on simulated data of the distributional properties of the item fit statistics that are commonly used in the Rasch model calibration programs as indices of the fit of responses to individual items to the measurement model. (SLD)

Ignorance of the characteristics of a mixed population may lead to bias in a summary measure of a phenomenon. A test based on sample kurtosis is demonstrated by a simulation study to be more powerful than six other known tests in detecting a class of mixed normal distributions. (SLD)

Standard maximum likeliheed estimation was compared using two forms of robust estimation, BIWEIGHT (based on Tukey's Biweight) and AMTJACK (AMT-Robustified Jackknife), and Rasch model person analysis. The two procedures recovered the generating parameters, but Rasch person analysis also helped to identify the nature of a response disturbance. (GDC)

Three correlation matrices (PEARSON, POLYCHORIC, and TOBIT) were used to obtain reliability estimates on ordered polytomous variable models. A Monte Carlo study with different levels of variable asymmetry and 400 sample correlation matrices demonstrated that the PEARSON matrix did not perform as well as did the other 2 matrices. (SLD)

Effects of the following variables on performance of computerized adaptive testing (CAT) procedures for the partial credit model (PCM) were studied: (1) stopping rule for terminating CAT; (2) item pool size; and (3) distribution of item difficulties. Implications of findings for CAT systems based on the PCM are discussed. (SLD)

Effects of dimensionality on ability estimation of an adaptive test were examined using generated data in Bayesian computerized adaptive testing (CAT) simulations. Generally, increasing interdimensional difficulty association produced a slight decrease in test length and an increase in accuracy of ability estimation as assessed by root mean square…