Characteristic curve approaches for linking parameters from the generalized partial credit model were examined for cases in which common (anchor) items are calibrated separately in two groups. Three of these approaches are simple extensions of the test characteristic curve (TCC), item characteristic curve (ICC), and operating characteristic curve…

Presents a method for estimating the random coefficients model using covariance structure modeling and allowing one to estimate both fixed and random effects. The method is applied to real and simulated data, including marriage data from J. Belsky and M. Rovine (1990). (SLD)

This paper describes the graded response model. The graded response model represents a family of mathematical models that deal with ordered polytomous categories, such as: (1) letter grading; (2) an attitude survey with "strongly disagree, disagree, agree, and strongly agree" choices; (3) partial credit given in accord with an…

It is shown that it is not easy to apply the EM algorithm to latent class models in the general case with equality constraints because a nonlinear equation has to be solved. A simpler condition is given in which the EM algorithm can be easily applied. (SLD)

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…

Latent class analysis is formulated as a problem of estimating parameters in a finite mixture distribution. The EM algorithm is used to find the maximum likelihood estimates, and the case of categorical variables with more than two categories is considered. (Author)

In this paper the parameter identifiability and estimation of a general dynamic structural model under indirect observation is considered from a system theoretic perspective. (Author/LMO)

A model which approaches the problem of characterizing distributions of test validity correlation coefficients from the perspective of finite mixture theory is presented. This estimation method offers advantages over validity generalization procedures. Examples are provided to illustrate applications of the method. (SLD)

The perturbation theory of the generalized eigenproblem is used to derive influence functions of each squared canonical correlation coefficient and the corresponding canonical vector pair. Three sample versions of these functions are described, and some properties are noted. Two obvious applications, multiple correlation and correspondence…

Multiple imputations for latent variables are constructed so that analyses treating them as true variables have the correct expectations for population characteristics. Analyzing multiple imputations in accordance with their construction yields correct estimates of population characteristics, whereas analyzing them as multiple indicators generally…

A new version of the standardized estimated parameter change that is invariant to the original metrics of the measured and latent variables is suggested for use in model modification. A multivariate estimated parameter change for a set of fixed parameters to be freed simultaneously is also introduced. (SLD)

Nonlinear latent variable models are specified that include quadratic forms and interactions of latent regressor variable as special cases. To estimate the parameters, the models are put in a Bayesian framework with conjugate priors for the parameters. The proposed estimation methods are illustrated by two simulation studies. (SLD)

Previous methods for estimating the conditional standard error of measurement (CSEM) at specific score or ability levels are critically discussed, and a brief summary of prior empirical results is given. A new method is developed which avoids theoretical problems inherent in some prior methods, is easy to implement, and estimates not only a…

Developed a multidimensional Rasch model that is a multidimensional extension of item component models and determined relations to existing multidimensional item response theory models. Applied the model to a questionnaire on students' interest in physics to demonstrate that model parameters can be estimated even when 17 latent dimensions are to…

A general approach is described for the analysis of categorical data when there are missing values on one or more observed variables. The method is based on generalized linear models with composite links. Situations in which the model can be used are described. (SLD)