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Reise, Steven P. – Multivariate Behavioral Research, 2012
Bifactor latent structures were introduced over 70 years ago, but only recently has bifactor modeling been rediscovered as an effective approach to modeling "construct-relevant" multidimensionality in a set of ordered categorical item responses. I begin by describing the Schmid-Leiman bifactor procedure (Schmid & Leiman, 1957) and highlight its…
Descriptors: Models, Factor Structure, Factor Analysis, Correlation
Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian – Multivariate Behavioral Research, 2011
Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…
Descriptors: Simulation, Factor Analysis, Item Response Theory, Models
Improvement in Detection of Differential Item Functioning Using a Mixture Item Response Theory Model
Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk – Multivariate Behavioral Research, 2010
Usually, methods for detection of differential item functioning (DIF) compare the functioning of items across manifest groups. However, the manifest groups with respect to which the items function differentially may not necessarily coincide with the true source of the bias. It is expected that DIF detection under a model that includes a latent DIF…
Descriptors: Test Bias, Item Response Theory, Models, Aptitude Tests
Fu, Zhi-Hui; Tao, Jian; Shi, Ning-Zhong; Zhang, Ming; Lin, Nan – Multivariate Behavioral Research, 2011
Multidimensional item response theory (MIRT) models can be applied to longitudinal educational surveys where a group of individuals are administered different tests over time with some common items. However, computational problems typically arise as the dimension of the latent variables increases. This is especially true when the latent variable…
Descriptors: Simulation, Foreign Countries, Longitudinal Studies, Item Response Theory
Ferrando, Pere J.; Anguiano-Carrasco, Cristina – Multivariate Behavioral Research, 2009
This article proposes a model-based multiple-group procedure for assessing the impact of faking on personality measures and the scores derived from these measures. The assessment is at the item level and the base model, which is intended for binary items, can be parameterized both as an Item Response Theory (IRT) model and as an Item…
Descriptors: Personality, Personality Measures, Item Response Theory, Deception
Maydeu-Olivares, Alberto; Brown, Anna – Multivariate Behavioral Research, 2010
The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…
Descriptors: Item Response Theory, Rating Scales, Models, Comparative Analysis
Hsieh, Chueh-An; von Eye, Alexander A.; Maier, Kimberly S. – Multivariate Behavioral Research, 2010
The application of multidimensional item response theory models to repeated observations has demonstrated great promise in developmental research. It allows researchers to take into consideration both the characteristics of item response and measurement error in longitudinal trajectory analysis, which improves the reliability and validity of the…
Descriptors: Item Response Theory, Change, Adolescents, Social Isolation
Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas – Multivariate Behavioral Research, 2011
The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…
Descriptors: Monte Carlo Methods, Patients, Probability, Item Response Theory
Lubke, Gitta; Neale, Michael – Multivariate Behavioral Research, 2008
Factor mixture models are latent variable models with categorical and continuous latent variables that can be used as a model-based approach to clustering. A previous article covered the results of a simulation study showing that in the absence of model violations, it is usually possible to choose the correct model when fitting a series of models…
Descriptors: Item Response Theory, Models, Likert Scales, Simulation
Chow, Sy-Miin; Ferrer, Emilio; Nesselroade, John R. – Multivariate Behavioral Research, 2007
In the past several decades, methodologies used to estimate nonlinear relationships among latent variables have been developed almost exclusively to fit cross-sectional models. We present a relatively new estimation approach, the unscented Kalman filter (UKF), and illustrate its potential as a tool for fitting nonlinear dynamic models in two ways:…
Descriptors: Item Response Theory, Models
Dinno, Alexis – Multivariate Behavioral Research, 2009
Horn's parallel analysis (PA) is the method of consensus in the literature on empirical methods for deciding how many components/factors to retain. Different authors have proposed various implementations of PA. Horn's seminal 1965 article, a 1996 article by Thompson and Daniel, and a 2004 article by Hayton, Allen, and Scarpello all make assertions…
Descriptors: Structural Equation Models, Item Response Theory, Computer Software, Surveys
Woods, Carol M. – Multivariate Behavioral Research, 2009
Differential item functioning (DIF) occurs when an item on a test or questionnaire has different measurement properties for 1 group of people versus another, irrespective of mean differences on the construct. This study focuses on the use of multiple-indicator multiple-cause (MIMIC) structural equation models for DIF testing, parameterized as item…
Descriptors: Test Bias, Structural Equation Models, Item Response Theory, Testing
Woods, Carol M. – Multivariate Behavioral Research, 2008
Person fit is the degree to which an item response model fits for individual examinees. Reise (2000) described how two-level logistic regression can be used to detect heterogeneity in person fit, evaluate potential predictors of person fit heterogeneity, and identify potentially aberrant individuals. The method has apparently never been applied to…
Descriptors: Simulation, Test Reliability, Measures (Individuals), Item Response Theory
Culpepper, Steven Andrew – Multivariate Behavioral Research, 2009
This study linked nonlinear profile analysis (NPA) of dichotomous responses with an existing family of item response theory models and generalized latent variable models (GLVM). The NPA method offers several benefits over previous internal profile analysis methods: (a) NPA is estimated with maximum likelihood in a GLVM framework rather than…
Descriptors: Profiles, Item Response Theory, Models, Maximum Likelihood Statistics

Ferrando, Pere J. – Multivariate Behavioral Research, 2002
Analyzed the relations between two continuous response models intended for typical response items: the linear congeneric model and Samejima's continuous response model (CRM). Illustrated the relations described using an empirical example and assessed the relations through a simulation study. (SLD)
Descriptors: Comparative Analysis, Item Response Theory, Models, Simulation
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