Full-Information Item Factor Analysis

Bock, R. Darrell; Gibbons, Robert D.; Muraki, Eiji

doi:10.1177/014662168801200305

Cited by 455 publications

(396 citation statements)

References 17 publications

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“…The relative importance of the ability dimensions for the responses to specific items is modeled by item-specific loadings a kq and the relation between the ability dimensions in some population of respondents is modeled by the correlation between the ability dimensions. The model can be estimated and tested by various maximum likelihood and Bayesian methods (Béguin & Glas, 2001 ;Bock, Gibbons & Muraki, 1988 ;Muthén, 1984).…”

Section: Measurement Error Modelsmentioning

confidence: 99%

Item response theory in educational assessment and evaluation

Glas

2014

mee

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Item response theory provides a useful and theoretically well-founded framework for educational measurement. It supports such activities as the construction of measurement instruments, linking and equating measurements, and evaluation of test bias and differential item functioning. It further provides underpinnings for item banking and flexible test administration designs, such as multiple matrix sampling, flexi-level testing, and computerized adaptive testing. First, a concise introduction to the principles of IRT models is given. The models discussed pertain to dichotomous items (items that are scored as either correct or incorrect) and polytomous items (items with partial credit scoring, such as most types of openended questions and performance assessments). Second, it is shown how an IRT measurement model can be enhanced with a structural model, such as, for instance, an analysis of variance model, to relate data from achievement and ability tests to students’ background variables, such as socio-economic status, intelligence or cultural capital, to school variables, and to features of the schooling system. Two applications are presented. The first one pertains to equating and linking of assessments, and the second one to a combination of an IRT measurement model and a multilevel linear model useful in school effectiveness research.La théorie de réponse à l’item (TRI) fournit un cadre utile et théoriquement bien fondé pour la mesure en éducation. Elle soutient des activités telles que la construction d’instruments de mesure, les procédures de mise en relation et de vérification d’équivalence des mesures, l’évaluation du biais d’un test et le fonctionnement différentiel d’items. Elle prévoit la base pour des banques d’items et des designs flexibles pour l’administration d’un test, comme les méthodes d’échantillonnage multicritérié, « flexi-level testing », et la méthode du test adaptatif par ordinateur. Tout d’abord, une brève introduction aux principes de modèles TRI est donnée. Les modèles discutés concernent des items dichotomiques (items qui sont corrects ou incorrects) et des items polytomiques (items à un crédit partiel, comme la plupart des questions ouvertes et questions de l’évaluation des compétences). Deuxièmement, on montre comment un modèle de mesure TRI peut être amélioré en utilisant un modèle structurel, par exemple, un modèle d’analyse de la variance, pour établir un lien entre les données provenant de tests pour mesurer le rendement et la capacité des élèves à des variables, tels leur statut socio-économique, leur niveau d’intelligence ou leur capital culturel, et à des variables caractérisant l’école et le système scolaire. Deux applications sont présentées. La première se rapporte aux procédures de type mise en parallèle (equating et linking), et la seconde à une combinaison d’un modèle de mesure TRI et d’un modèle linéaire multiniveaux utilisé dans la recherche relative à l’efficacité de l’école.A teoria de resposta ao item (TRI) fornece um quadro útil e teoricamente bem fundamentado para a...

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Section: Measurement Error Modelsmentioning

confidence: 99%

Item response theory in educational assessment and evaluation

Glas

2014

mee

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“…A primary reason for the multidimensionality of psychiatric measurement scales is that items are often sampled from multiple domains (for example, various mood disorders). Bock and colleagues (11,12) extended the item response theory model to the multidimensional case, where each item is related to multiple underlying factors. Despite the availability of these item response theory models (11)(12)(13)(14), they have not been well studied in the context of CAT.…”

Section: :361-368 2008)mentioning

confidence: 99%

“…Bock and colleagues (11,12) extended the item response theory model to the multidimensional case, where each item is related to multiple underlying factors. Despite the availability of these item response theory models (11)(12)(13)(14), they have not been well studied in the context of CAT. A major limitation of multidimensional CAT is that it involves selection of items that will increase precision of measurement simultaneously on all dimensions of interest.…”

Section: :361-368 2008)mentioning

confidence: 99%

Mental Health Assessment

Cox¹,

Turner²,

Blackwood³

2004

Physical Assessment for Nurses

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“…This latent variable is akin to a factor in a factor analysis model for continuous variables, and so IRT and factor analysis models are also very much related; a useful source for this is Bartholomew and Knott [1999]. Because a test or scale can measure more than one latent factor, multidimensional IRT models have also been developed [Bock et al, 1988, Gibbons andHedeker, 1992]; the collection by van der Linden and Hambleton [1997] presents some of these developments.…”

Section: Introductionmentioning

confidence: 99%

Application of Item Response Theory Models for Intensive Longitudinal Data

Hedeker

Mermelstein

Flay

2006

Models for Intensive Longitudinal Data

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SummaryItem Response Theory (IRT) models, also called latent trait models, have been extensively used in educational testing and psychological measurement. While an IRT model is essentially a mixed-effects regression model for longitudinal categorical data, use of IRT has been somewhat limited outside of education and psychology.In this chapter, we describe IRT models and some key developments in the IRT literature, and illustrate their application for intensive longitudinal data. In particular, we relate IRT models to mixed models and indicate how software for the latter can be used to estimate the IRT model parameters. Using Ecological Momentary Assessment (EMA) data from a study of adolescent smoking, we describe how IRT models can be used to address key questions in smoking research.

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Full-Information Item Factor Analysis

Cited by 455 publications

References 17 publications

Item response theory in educational assessment and evaluation

Item response theory in educational assessment and evaluation

Mental Health Assessment

Application of Item Response Theory Models for Intensive Longitudinal Data

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