E.J. Bedrick recently derived the asymptotic distribution of the modified sample biserial correlation estimator of F.M. Lord and studied its efficacy for bivariate normal populations. A more detailed examination of the properties of Lord's estimator is provided, and the small sample bias and variance are studied. (SLD)

Information functions are used to find the optimum ability levels and maximum contributions to information for estimating item parameters in three commonly used logistic item response models. Implications are discussed for applications such as adaptive testing and test construction. (SLD)

A new computerized mastery test is described that builds on the Lewis and Sheehan procedure (sequential testlets) (1990), but uses fuzzy set decision theory to determine stopping rules and the Rasch model to calibrate items and estimate abilities. Differences between fuzzy set and Bayesian methods are illustrated through an example. (SLD)

This paper examines the effect of using unidimensional item response theory (IRT) item parameter estimates of multidimensional items to create weakly parallel test forms using target information curves. To date, all computer-based algorithms that have been devised to create parallel test forms assume that the items are unidimensional. This paper…

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…

A polychotomous nominal response model-based computerized adaptive test (CAT) was simulated using data from 1,093 University of Texas students. The ability estimation of this model and its overall performance were compared with those of a dichotomous three-parameter logistic model-based CAT. Advantages and drawbacks of nominal response CAT are…

Conjunctive item response models are introduced such that (a) sufficient statistics for latent traits are not necessarily additive in item scores; (b) items are not necessarily locally independent; and (c) existing compensatory (additive) item response models including the binomial, Rasch, logistic, and general locally independent model are…

Using raw-to-scaled-score conversions derived from test-score equating to link item-parameter estimates from the one-parameter (Rasch) and three-parameter logistic models, this study evaluated an indirect method for converting item response theory estimates to a common scale. Data were taken from Petersen's Scholastic Aptitude Test (SAT) scale…

The usefulness of the confirmatory factor analysis model of D. Sorbom (1974) to estimate invariant difficulty and discrimination item parameters on a personality scale was supported in a study using responses of 834 undergraduates to the Social Worry Scale of the Anxious Thoughts Inventory (A. Wells, 1994). (SLD)

To investigate the effect on item parameter estimation of pooling the raters' ratings and to examine the information content of 2 types of writing samples, the partial credit model was fit to 2,000 writing samples from secondary students that had been holistically scored. Implications for test construction are discussed. (SLD)

In a preceding research report, ONR/RR-82-1 (Information Loss Caused by Noise in Models for Dichotomous Items), observations were made on the effect of noise accommodated in different types of models on the dichotomous response level. In the present paper, focus is put upon the three-parameter logistic model, which is widely used among…

One of the important underlying assumptions of all item response theory (IRT) models is that of local independence. This assumption requires that the response to an item on a test not be influenced by the response to any other items. This assumption is often taken for granted, with little or no scrutiny of the response process required to answer…

Two optimalization models for the construction of tests with a maximal value of coefficient alpha are given. Both models have a linear form and can be solved by using a branch-and-bound algorithm. The first model assumes an item bank calibrated under the Rasch model and can be used, for instance, when classical test theory has to serve as an…

The PARallELogram Analysis (PARELLA) model is a probabilistic parallelogram model that can be used for the measurement of latent attitudes or latent preferences. A method is presented for testing for differential item functioning (DIF) for the PARELLA model using the approach of D. Thissen and others (1988). (SLD)

The derivation of several item selection algorithms for use in fitting test items to target information functions is described. These algorithms circumvent iterative solutions by using the criteria of moving averages of the distance to a target information function and simultaneously considering an entire range of ability points used to condition…