Developed an EM type algorithm for maximum likelihood estimation of a general nonlinear structural equation model in which the E-step is completed by a Metropolis-Hastings algorithm. Illustrated the methodology with results from a simulation study and two real examples using data from previous studies. (SLD)

Proposes a two-stage estimation method for the analysis of covariance structure models with ordinal ipsative data (OID). A goodness-of-fit statistic is given for testing the hypothesized covariance structure matrix, and simulation results show that the method works well with a large sample. (SLD)

Properties of the pseudolikelihood method of estimating Rasch model item parameters, which is based on comparing responses to pairs of items without regard to other items, are studied. Simulation found pseudolikelihood estimates comparable to conditional and marginal maximum likelihood estimates. (SLD)

Studied the maximum likelihood estimation of unknown parameters in a general LISREL-type model with mixed polytomous and continuous data through Monte Carlo simulation. Proposes a model selection procedure for obtaining good models for the underlying substantive theory and discusses the effectiveness of the proposed model. (SLD)

In psychometrics, it is often the case that one encounters data that may not be considered random but selected in a systematic way according to some explanatory variable. In this article, maximum likelihood estimation is considered when data are supposed to arise from a bivariate normal distribution that is truncated in an extreme way. Two methods…

It is common to assume during statistical analysis of a multiscale assessment that the assessment has simple structure or that it is composed of several unidimensional subtests. Under this assumption, both the unidimensional and multidimensional approaches can be used to estimate item parameters. This paper theoretically demonstrates that these…

Discusses fitting multivariate normal mixture distributions to structural equation modeling. The model used is a LISREL submodel that includes confirmatory factor and structural equation models. Two approaches to maximum likelihood estimation are used. A simulation study compares confidence intervals based on the observed information and…

The Rasch Poisson counts model is a latent trait model for the situation in which "K" tests are administered to "N" examinees and the test score is a count (repeated number of some event). A mixed model is presented that applies the EM algorithm and that can allow for missing data. (SLD)

This paper investigates methods that avoid using multiple groups to represent the missing data patterns in covariance structure modeling, attempting instead to do a single-group analysis where the only action the analyst has to take is to indicate that data is missing. A new covariance structure approach developed by B. Muthen and G. Arminger is…

This study investigated the effect on examinees' ability estimate under item response theory (IRT) when they are presented an item, have ample time to answer the item, but decide not to respond to the item. Simulation data were modeled on an empirical data set of 25,546 examinees that was calibrated using the 3-parameter logistic model. The study…

Selectivity problems are discussed in terms of a general model that is estimated by the maximum likelihood method. Both single-group and multiple-group analyses are considered. An extension of the general model to latent variable models is discussed. (Author/PN)

A simulation study was conducted to investigate the application of expected a posteriori (EAP) trait estimation in computerized adaptive tests (CAT) based on the partial credit model and compare it with maximum likelihood estimation (MLE). Results show the conditions under which EAP and MLE provide relatively accurate estimation in CAT. (SLD)

Through a large-scale simulation study, this article compares item parameter estimates obtained by the marginal maximum likelihood estimation (MMLE) and marginal Bayes modal estimation (MBME) procedures in the 3-parameter logistic model. The impact of different prior specifications on the MBME estimates is also investigated using carefully…

We illustrate a class of multidimensional item response theory models in which the items are allowed to have different discriminating power and the latent traits are represented through a vector having a discrete distribution. We also show how the hypothesis of unidimensionality may be tested against a specific bidimensional alternative by using a…

Research discussed in this paper was conducted as part of an ongoing large-scale simulation study to evaluate methods of calibrating pretest items for computerized adaptive testing (CAT) pools. The simulation was designed to mimic the operational CAT Armed Services Vocational Aptitude Battery (ASVAB) testing program, in which a single pretest item…