Application of MIRT modeling procedures is dependent on the quality of parameter estimates provided by the estimation software and techniques used. This study investigated model parameter recovery of two popular MIRT packages, BMIRT and flexMIRT, under some common measurement conditions. These packages were specifically selected to investigate the…

As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…

DETECT is a nonparametric "full" dimensionality assessment procedure that clusters dichotomously scored items into dimensions and provides a DETECT index of magnitude of multidimensionality. Four factors (test length, sample size, item response theory [IRT] model, and DETECT index) were manipulated in a Monte Carlo study of bias, standard error,…

The purpose of the present research was to study, systematically, the "goodness-of-fit" of the one-, two-, and three-parameter logistic models. We studied, using computer-simulated test data, the effects of four variables: variation in item discrimination parameters, the average value of the pseudo-chance level parameters, test length,…

A new method was developed to assist in the selection of a test length by utilizing computer simulation procedures and item response theory. A demonstration of the method presents results which address the influences of item pool heterogeneity matched to the objectives of interest and the method of item selection. (Author/PN)

The impact of capitalizing on chance in item selection on the accuracy of test information functions was studied through simulation, focusing on examinee sample size in item calibration and the ratio of item bank size to test length. (SLD)

Addressing the shortcomings of classical item statistics for selecting criterion-referenced test items, this paper describes an optimal item selection procedure utilizing item response theory (IRT) and offers examples in which random selection and optimal item selection methods are compared. Theoretical advantages of optimal selection based upon…

The study compared two promising item response theory (IRT) item-selection methods, optimal and content-optimal, with two non-IRT item selection methods, random and classical, for use in fixed-length certification exams. The four methods were used to construct 20-item exams from a pool of approximately 250 items taken from a 1985 certification…