Any item response theory (IRT) researcher or practitioner will find something of interest in this book, which covers a broad range of topics in essays by well-known researchers. Chapters are organized into sections devoted to parametric and nonparametric IRT topics. (SLD)

This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)

This paper argues that: test data are ordinal; latent trait scores are only determined ordinally; and test data are used largely for ordinal purposes. A set of ordinal assumptions is presented, including an ordinal version of local independence. It is concluded that a purely ordinal test theory is possible. (TJH)

A general dichotomous condition is derived for the unidimensional polytomous Rasch model. The robustness of the dichotomous analysis is investigated in a simulation study. The model shows a close relation with the two-parameter Birnbaum model. (TJH)

A similarity-based smoothing approach to nondimensional item analysis was studied. Simulated and actual data are presented to show that when responses are determined by a latent ability variable, this similarity-based smoothing procedure can reveal the dimensionality of ability satisfactorily. (SLD)

A multiobjective programming method is proposed for determining samples of examinees needed for estimating the parameters of a group of items. This approach maximizes the information functions of each of three parameters. A numerical verification of the procedure is presented. (SLD)

A family of coefficients of relational agreement for numerical scales is proposed, generalizing to multiple judges the theory of F. E. Zegers and J. M. F. ten Berge (1985) of association coefficients for two variables, using the premise that choice of coefficient depends on scale type of the variables. (SLD)

Characterizations of local homogeneity and the homogeneous monotone item response theory (IRT) model are provided. The characterization theorem states that the joint condition of experimental independence and pairwise nonnegative association in every nonnegligible subpopulation is necessary and sufficient for the homogenous monotone IRT model.…

A necessary and sufficient condition is given in this paper for the existence and uniqueness of the maximum likelihood (the so-called joint maximum likelihood) estimate of the parameters of the Partial Credit Model. This condition is stated in terms of a structural property of the pattern of the data matrix that can be easily verified on the basis…

In many instances it is reasonable to assume that the population covariance matrix has positive elements. This assumption implies for the single factor analysis model that the loadings and regression weights for best linear factor prediction are positive. For the multiple factor analysis model where each variable loads on a single factor and a…

The maximum and minimum of a sample from a probability distribution are extremely important random variables in many areas of psychological theory, methodology, and statistics. For instance, the behavior of the mean of the maximum or minimum processing time, as a function of the number of component random processing times ("n"), has been studied…

This paper extends the theory of conditional covariances to polytomous items. It has been proven that under some mild conditions, commonly assumed in the analysis of response data, the conditional covariance of two items, dichotomously or polytomously scored, given an appropriately chosen composite is positive if, and only if, the two items…

Nonparametric item response models have been developed as alternatives to the relatively inflexible parametric item response models. An open question is whether it is possible and practical to administer computerized adaptive testing with nonparametric models. This paper explores the possibility of computerized adaptive testing when using…

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

A nonparametric multicategorical model for multiple-choice data is proposed as an extension of the binary spline model of J. O. Ramsay and M. Abrahamowicz (1989). Results of two Monte Carlo studies illustrate the model, which approximates probability functions by rational splines. (SLD)