A marginal maximum a posteriori (MMAP) procedure was implemented to estimate item parameters in the generalized graded unfolding model (GGUM). Estimates from the MMAP method were compared with those derived from marginal maximum likelihood (MML) and Markov chain Monte Carlo (MCMC) procedures in a recovery simulation that varied sample size,…

Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…

Assessments consisting of different domains (e.g., content areas, objectives) are typically multidimensional in nature but are commonly assumed to be unidimensional for estimation purposes. The different domains of these assessments are further treated as multi-unidimensional tests for the purpose of obtaining diagnostic information. However, when…

DETECT is a nonparametric "full" dimensionality assessment procedure that clusters dichotomously scored items into dimensions and provides a DETECT index of magnitude of multidimensionality. Four factors (test length, sample size, item response theory [IRT] model, and DETECT index) were manipulated in a Monte Carlo study of bias, standard error,…

The accuracy of estimation procedures in item response theory was studied using Monte Carlo methods and varying sample size, number of subjects, and distribution of ability parameters for: (1) joint maximum likelihood as implemented in the computer program LOGIST; (2) marginal maximum likelihood; and (3) marginal Bayesian procedures as implemented…

TAILOR, a computer program which implements an approach to tailored testing, was examined by Monte Carlo methods. The evaluation showed the procedure to be highly reliable and capable of reducing the required number of tests items by about one half. (Author/JKS)

Studied the extent to which three appropriateness indexes, Z(sub 3), ECIZ4, and W, are well standardized in a Monte Carlo study. The ECIZ4 most closely approximated a normal distribution, and its skewness and kurtosis were more stable and less affected by test length and item response theory model than the others. (SLD)

Monte Carlo methods are used to evaluate marginal maximum likelihood estimation of item parameters and maximum likelihood estimates of theta in the two-parameter logistic model for varying test lengths, sample sizes, and assumed theta distributions. Results with 100 datasets demonstrate the methods' general precision and stability. Exceptions are…

Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)

Effects of test length, sample size, and assumed ability distribution were investigated in a multiple replication Monte Carlo study under the 1-parameter (1P) and 2-parameter (2P) logistic graded model with five score levels. Accuracy and variability of item parameter and ability estimates were examined. Monte Carlo methods were used to evaluate…

This study compares the ability of the multiple indicators, multiple causes (MIMIC) confirmatory factor analysis model to correctly identify cases of differential item functioning (DIF) with more established methods. Although the MIMIC model might have application in identifying DIF for multiple grouping variables, there has been little…

This study investigates item parameter recovery, standard error estimates, and fit statistics yielded by the WINSTEPS program under the Rasch model and the rating scale model through Monte Carlo simulations. The independent variables were item response model, test length, and sample size. WINSTEPS yielded practically unbiased estimates for the…

A two-stage testing strategy is one method of adapting the difficulty of a test to an individual's ability level in an effort to achieve more precise measurement. A routing test provides an initial estimate of ability level, and a second-stage measurement test then evaluates the examinee further. The measurement accuracy and efficiency of item…

Forming the matching variable for the Mantel-Haenszel differential item functioning (DIF) procedure through use of the total score as the matching variable (thin) and forming the matching variable by pooling total score levels (thick) were compared in a Monte Carlo study. Reasons thick matching is superior are discussed. (SLD)