Discusses two forms of separability of item and person parameters in the context of response time models. The first is "separate sufficiency," and the second is "ranking independence." For each form a theorem stating sufficient conditions is proved. The two forms are shown to include several cases of models from psychometric…

An approach is presented for determining unidimensional scale estimates that are relatively insensitive to limited inconsistencies in paired comparisons data. The solution procedure--a minimum-cost network-flow problem--is presented in conjunction with a sensitivity diagnostic that assesses the influence of a single pairwise comparison on…

The problems posed for latent variable analysis by populations with different sets of parameter values are discussed. An overview of methodology to address heterogeneity is presented, including a review of structural modeling by the multiple indicator-multiple causes model and the use of the LISCOMP computer program. (SLD)

Misspecification of mean and covariance structures for metric endogenous variables is considered. Maximum likelihood estimation of model parameters and the asymptotic covariance matrix of the estimates are discussed. A Haussman test for misspecification is developed, which is sensitive to misspecification not detected by the test statistics…

An item-response model for binary response data exhibiting the bi-factor structure is derived, and a practical parameter estimation method is developed. The model, which provides an alternate to the traditional conditionally independent unidimensional item response theory model, is illustrated with an example from psychiatric research. (SLD)

This paper reports an attempt to identify appropriate and robust location estimators for situations that tend to occur among various types of empirical data. Emphasizing robustness across broad unidentifiable ranges of contamination, an attempt was made to replicate, on a somewhat smaller scale, the definitive Princeton Robustness Study of 1972 to…

A method of comparing one-step M-estimates of location for heavy tailed distributions is proposed and investigated. Simulations indicate that the new procedure provides good control over Type I errors and has more power than do some other methods for dealing with heavy tailed distributions. (SLD)

An example of scale invariance is provided via the LISREL model that is subject only to classical normalizations and zero constraints on the parameters. Scale invariance implies that the estimated covariance matrix must satisfy certain equations, and the nature of these equations depends on the fitting function used. (TJH)

The models and procedures discussed in this paper are related to those presented in Bock and Aitkin (1981), where they considered the 2-parameter probit model and approximated a normally distributed prior distribution of abilities by a finite and discrete distribution. One purpose of this paper is to clarify the nature of the general EM (GEM)…

Based on the usual factor analysis model, this paper investigates the relationship between improper solutions and the number of factors. The properties of the noniterative estimation method of M. Ihara and Y. Kano in exploratory factor analysis are also discussed. The estimators were compared in a Monte Carlo experiment. (TJH)

Using Monte Carlo methods, the applicability of large sample theory to maximum likelihood estimates of total indirect effects in sample sizes of 50, 100, 200, 400, and 800 was studied. Samples of at least 200 and 400 are required for the recursive and nonrecursive models, respectively, that were assessed. (TJH)

A probabilistic choice model, based on L. L. Thurstone's Law of Comparative Judgment Case V, is developed for paired comparisons data about psychological stimuli. The model assumes that each stimulus is measured on a small number of physical variables. An algorithm for estimating parameters is illustrated with real data. (SLD)

A class of models is presented for gamma distributed random variables. These additive, multiplicative, and combined additive-multiplicative models are more flexible than classical linear models with respect to the structure that can be imposed on expected values. As a special case, a class of psychometric models for reaction times is presented.…

Binary or graded disagree-agree responses to attitude items are often collected for the purpose of attitude measurement. Although such data are sometimes analyzed with cumulative measurement models, recent investigations suggest that unfolding models are more appropriate (J. S. Roberts, 1995; W. H. Van Schuur and H. A. L. Kiers, 1994). Advances in…

In three lectures, Benjamin D. Wright of the University of Chicago introduces the Rasch model and its basic concepts. The first lecture, March 30, 1994 discusses the model created by Georg Rasch, a Danish mathematician, which Dr. Wright initially saw as merely a way to make raw scores into measures. Eventually, the model developed into a…