Item characteristic curve (ICC) theory describes the relationship between the ability of individuals and the probability of their answering a test question correctly; it is useful in estimating test scores, equating the scores of various tests, and scoring responses during adaptive testing. A simulation study of the effectiveness of the following…

A study was conducted to compare the quality of the item parameter estimates obtained from the ANCILLES and LOGIST estimation procedures using goodness of fit as a criterion. Statistics used to compare the fit included a chi-square statistic and a mean square deviation statistic. Other analyses performed included comparisons of the distributions…

Using one simulated and two real data sets, the effects of the systematic variation of the item-selection procedure and the stepsize method on the operating characteristics of computerized adaptive testing (CAT) for instruments with polychotomously scored rating scale items were studied. The six rating scale CAT procedures used performed well.…

The recovery of weak factors has been extensively studied in the context of exploratory factor analysis. This article presents the results of a Monte Carlo simulation study of recovery of weak factor loadings in confirmatory factor analysis under conditions of estimation method (maximum likelihood vs. unweighted least squares), sample size,…

In this paper a Bayesian procedure is developed for the simultaneous estimation of the reading ability and difficulty parameters which are assumed to be factors in reading errors by the multiplicative Poisson Model. According to several criteria, the Bayesian estimates are better than comparable maximum likelihood estimates. (Author/JAZ)

Standard maximum likeliheed estimation was compared using two forms of robust estimation, BIWEIGHT (based on Tukey's Biweight) and AMTJACK (AMT-Robustified Jackknife), and Rasch model person analysis. The two procedures recovered the generating parameters, but Rasch person analysis also helped to identify the nature of a response disturbance. (GDC)

The effects of priors and amount of bias in the Bayesian approach to the estimation problem in item response models are examined using simulation studies. Different specifications of prior information have only modest effects on Bayesian estimates, which are less biased than joint maximum likelihood estimates for small samples. (TJH)

The most useful method of item selection for making pass-fail decisions with a Computerized Adaptive Test (CAT) was studied. Medical technology students (n=86) took a computer adaptive test in which items were targeted to the ability of the examinee. The adaptive algorithm that selected items and estimated person measures used the Rasch model and…

Despite advances in common factor analysis, a review of 89 studies published in four selected journals between 1963 and 1976 indicated that behavioral scientists preferred principal components analysis, followed by varimax or orthogonal rotation. Resultant row sums of squares of factor matrices from principal component analyses of real data sets…

A modified regression procedure for finding a common metric for item response theory (IRT) parameter estimates and for total test scores is proposed and compared to the chi-square method of equating. The chi-square method was chosen after literature review for the currently used scaling procedures. The modification used with the regression…

Three methods of estimating test score distributions that may improve on using the observed frequencies (OBFs) as estimates of a population test score distribution are considered: the kernel method (KM); the polynomial method (PM); and the four-parameter beta binomial method (FPBBM). The assumption each method makes about the smoothness of the…

A hierarchical latent regression model is suggested to estimate nested and nonnested relationships in complex samples such as found in the National Assessment of Educational Progress (NAEP). The proposed model aims at improving both parameters and variance estimates via a two-level hierarchical linear model. This model falls naturally within the…

This paper reviews the literature about item response models for the subject level and aggregated level (group level). Group-level item response models (IRMs) are used in the United States in large-scale assessment programs such as the National Assessment of Educational Progress and the California Assessment Program. In the Netherlands, these…

This report describes a study comparing the classification results obtained from a one-parameter and three-parameter logistic based tailored testing procedure used in conjunction with Wald's sequential probability ratio test (SPRT). Eighty-eight college students were classified into four grade categories using achievement test results obtained…

The focus of this study is on the estimation procedures implemented in BILOG, a computer program. One purpose is to compare the item parameter estimates produced by various procedures available in BILOG. Four different models are used: the one, two, and three parameter model and a three parameter model with common guessing parameters. The results…