The unconditional--simultaneous--maximum likelihood (UML) estimation procedure for the one-parameter logistic model produces biased estimators. The UML method is inconsistent and is not a good alternative to conditional maximum likelihood method, at least with small numbers of items. The minimum Chi-square estimation procedure produces unbiased…

The effect of violating the assumption of nonspeededness on ability and item parameter estimates in item response theory was studied through simulation under three speededness conditions. Results indicate that ability estimation was least affected by speededness but that substantial effects on item parameter estimates were found. (SLD)

Effectiveness of jackknife methods in reducing bias in estimation of the log-1 autocorrelation parameter p1 was evaluated through a Monte Carlo study using sample sizes ranging from 6 to 500. These estimates appear less biased in the small sample case than many that have been investigated recently. (SLD)

The consequences of underextracting factors and components within and between the methods of maximum likelihood factor analysis and principal components analysis were examined through computer simulation. The principal components score and the factor score estimate (T. W. Anderson and H. Rubin, 1956) tended to become different with…

A simulation study by B. D. Wright and G. A. Douglas is critiqued, which indicates that the unconditional maximum likelihood method is an appropriate substitute for the theoretically superior conditional method for estimating parameters of the Rasch model. The study appears to rest on inadequate logic. (TJH)

The theoretical approaches taken by the LOGIST and BILOG computer programs for estimating the parameters of the three-parameter logistic item response model, and their practical consequences, are compared. Guidelines for choosing between the programs for particular applications are offered. (SLD)

The predicted scores produced by regression with (1) single best predictor, (2) two best predictors, (3) all predictors with observed values, and (4) all predictors with or without observed values were compared with variable means as estimates of missing values. The study was conducted in a simulation mode on nx8 data matrices using various levels…

The purpose of this study was to assess the effects of correlated dimensions and differential ability on one dimension on parameter estimation when using a two-dimensional item response theory model. Multidimensional analysis of simulated two-dimensional item response data fitting the M2PL model of M. D. Reckase (1985, 1986) was conducted using…

Parameter recovery in the graded-response model was investigated using the MULTILOG computer program under default conditions. Results from 36 simulated data sets suggest that at least 500 examinees are needed to achieve adequate calibration under the graded model. Sample size had little influence on the true ability parameter's recovery. (SLD)

The distinction between deterministic and statistical reasoning in the application of models to educational measurement is explicated. Issues addressed include the relationship between data and estimation equations, distinction between parameters and parameter estimates, and power of tests of fit of responses across the ability continuum. (TJH)

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.…

Using computer simulation data, the effect of a single global outlier in two-group classification analysis was explored in terms of the outcome variables of change in classification results (PCHNG), change in misclassification rate (MISDIF), and change in precision of misclassification rate estimation. The precision of misclassification rate…

Some effects of using unidimensional item response theory (IRT) were examined when the assumption of unidimensionality was violated. Adaptive and nonadaptive tests were used. It appears that use of a unidimensional model can bias parameter estimation, adaptive item selection, and ability estimation for the two types of testing. (TJH)

Using a Monte Carlo simulation, a bootstrap procedure was evaluated for setting a confidence interval on the unrestricted population correlation (rho) assuming various degrees of incomplete truncation on the predictor. Sample size was the most important factor in determining accuracy and stability. Sample size should be at least 50. (SLD)

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)