A single-step maximum likelihood estimation procedure is developed for multidimensional scaling of dissimilarity data measured on rating scales. The procedure can fit the euclidian distance model to the data under various assumptions about category widths and under two distributional assumptions. Practical uses of the method are demonstrated.…

Necessary and sufficient conditions for the existence and uniqueness of a solution of the so-called "unconditional" and the "conditional" maximum-likelihood estimation equations in the dichotomous Rasch model are given. It is shown how to apply the results in practical uses of the Rasch model. (Author/JKS)

A jackknife-like procedure is developed for producing standard errors of estimate in maximum likelihood factor analysis. Unlike earlier methods based on information theory, the procedure developed is computationally feasible on larger problems. Examples are given to demonstrate the feasibility of the method. (Author/JKS)

The distribution theory underlying corrections for guessing is analyzed, and the probability distributions of the random variables are derived. The correction in grade, based on random guessing of unknown answers, is compared with corrections based on educated guessing. (Author/MH)

Developed two methods for estimating the individual level correlation coefficient that combines information from aggregate data with a small fraction of the individual level data. Results of a simulation study support the use of these methods. (SLD)

This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

The mixture index of fit (T. Rudas et al, 1994) is used to estimate the fraction of a population for which differential item functioning (DIF) occurs, and this approach is compared to the Mantel Haenszel test of DIF. The proposed noniterative procedure provides information about data portions contributing to DIF. (SLD)

Compared approaches to determining the precision of gain scores: (1) the asymptotic normal distribution of the maximum likelihood estimator of the person parameter; and (2) the exact conditional distribution of the gain score. Use of three data sets illustrates that these methods yield more relevant and more detailed information than traditional…

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 class of locally dependent latent trait models for responses to psychological and educational tests. Focuses on models based on a family of conditional distributions, or kernel, that describes joint multiple item responses as a function of student latent trait, not assuming conditional independence. Also proposes an EM algorithm for…

Two methods of estimating parameters in the Rasch model are compared. The equivalence of likelihood estimations from the model of G. J. Mellenbergh and P. Vijn (1981) and from usual unconditional maximum likelihood (UML) estimation is demonstrated. Mellenbergh and Vijn's model is a convenient method of calculating UML estimates. (SLD)

The existence of higher-order factors within the cognition and convergent production operations and product dimensions of the structure-of-intellect model of J. P. Guilford was investigated. Data from 240 aviation officer candidates and Naval air cadets were reanalyzed via maximum likelihood confirmatory factor analysis, using the LISREL program.…

Some psychometric models are presented that belong to the larger class of latent response models (LRMs). Following general discussion of LRMs, a method for obtaining maximum likelihood and some maximum "a posteriori" estimates of the parameters of LRMs is presented and applied to the conjunctive Rasch model. (SLD)

This paper presents a new procedure called TREEFAM for estimating ultrametric tree structures from proximity data confounded by differential stimulus familiarity. The objective is to quantitatively filter out effects of stimulus unfamiliarity. Superiority of TREEFAM over conventional methods is illustrated through a Monte Carlo study and an…

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)