Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed…

As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores, including…

An assessment of graphic literacy was developed by articulating and subsequently validating a skills-based cognitive model intended to substantiate the plausibility of score interpretations. Model validation involved use of multiple sources of evidence derived from large-scale field testing and cognitive labs studies. Data from large-scale field…

Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…

Mixture Rasch models have been used to study a number of psychometric issues such as goodness of fit, response strategy differences, strategy shifts, and multidimensionality. Although these models offer the potential for improving understanding of the latent variables being measured, under some conditions overextraction of latent classes may…

As with any psychometric models, the validity of inferences from cognitive diagnosis models (CDMs) determines the extent to which these models can be useful. For inferences from CDMs to be valid, it is crucial that the fit of the model to the data is ascertained. Based on a simulation study, this study investigated the sensitivity of various fit…

A practical concern for many existing tests is that subscore test lengths are too short to provide reliable and meaningful measurement. A possible method of improving the subscale reliability and validity would be to make use of collateral information provided by items from other subscales of the same test. To this end, the purpose of this article…

The purpose of this study is to apply the attribute hierarchy method (AHM) to a subset of SAT critical reading items and illustrate how the method can be used to promote cognitive diagnostic inferences. The AHM is a psychometric procedure for classifying examinees' test item responses into a set of attribute mastery patterns associated with…

This article demonstrates the use of a new class of model-free cumulative sum (CUSUM) statistics to detect person fit given the responses to a linear test. The fundamental statistic being accumulated is the likelihood ratio of two probabilities. The detection performance of this CUSUM scheme is compared to other model-free person-fit statistics…

This article describes a latent trait approach to skills diagnosis based on a particular variety of latent class models that employ item response functions (IRFs) as in typical item response theory (IRT) models. To enable and encourage comparisons with other approaches, this description is provided in terms of the main components of any…

A Monte Carlo simulation technique for generating dichotomous item scores is presented that implements (a) a psychometric model with different explicit assumptions than traditional parametric item response theory (IRT) models, and (b) item characteristic curves without restrictive assumptions concerning mathematical form. The four-parameter beta…

The purpose of this paper is to describe the logic and identify key assumptions associated with making cognitive inferences using two attribute-based psychometric methods. The first method is Kikumi Tatsuoka's rule-space model. This model provides a strong point of reference for studying the nature of diagnostic inferences because it is important…

Consider test data, a specified set of dichotomous skills measured by the test, and an IRT cognitive diagnosis model (ICDM). Statistical estimation of the data set using the ICDM can provide examinee estimates of mastery for these skills, referred to generally as attributes. With such detailed information about each examinee, future instruction…

The Petersen-Novick paper dealing with culture fair selection (TM 502 259) is the basis for this article. The author proposes a perspective in which ideas can be lined up for comparison and suggests solutions to the problems of selection in employment. (DEP)

This book provides a historical overview of item-response theory (IRT) and contains a compendium of item-response-theory research. Each of its six sections deals with a unique application of a model or a family of models. Requires a strong psychometric background to understand some of the discussions. (SLD)