Item Response Theory

Embretson, Susan E.; Reise, Steven P.

doi:10.4324/9781410605269

Cited by 1,512 publications

(2,042 citation statements)

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“…SEM has moved us from examining simple correlation patterns between a predictor and criterion measure or from descriptions of static personality factors (e.g., FFM À see Cattell, Boyle, & Chant, 2002), to testing competing structural models of trait constructs in dynamic patterns of cause and effect and moderating and mediating relationships with other factors. Item response theory (IRT; Embretson & Reise, 2000), based on formal modeling of the influence of person and item parameters on test responses has also become increasingly influential in assessment.…”

Section: Validitymentioning

confidence: 99%

Criteria for Selection and Evaluation of Scales and Measures

Boyle¹,

Saklofske²,

Matthews³

2015

Measures of Personality and Social Psychological Constructs

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Section: Validitymentioning

confidence: 99%

Criteria for Selection and Evaluation of Scales and Measures

Boyle¹,

Saklofske²,

Matthews³

2015

Measures of Personality and Social Psychological Constructs

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“…measured) variables and latent (i.e. unmeasured) constructs while accounting for measurement properties and error in the analyses (Embretson & Reise, 2000).…”

Section: Resultsmentioning

confidence: 99%

The Prenatal Distress Questionnaire: an investigation of factor structure in a high risk population

Alderdice

Savage-McGlynn²,

Martin

et al. 2013

Journal of Reproductive and Infant Psychology

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Background: The Prenatal Distress Questionnaire (PDQ) is a short measure designed to assess specific worries and concerns related to pregnancy. The aim of this study was to confirm the factor structure of the PDQ in a group of pregnant women with a small for gestational age infant (< 10th centile). Methods: The first PDQ assessment for each of 337 pregnant women participating in the Prospective Observational Trial to Optimise paediatric health (PORTO) study was analysed. All women enrolled in the study were identified as having a small for gestational age foetus (< 10th centile), thus representing an 'elevated risk' group. Data were analysed using confirmatory factor analysis (CFA). Three models of the PDQ were evaluated and compared in the current study: a theoretical uni-dimensional measurement model, a bi-dimensional model, and a threefactor model solution. Results: The three-factor model offered the best fit to the data while maintaining sound theoretical grounds(χ 2 (51df) = 128.52; CFI = 0.97; TLI = 0.96; RMSEA = 0.07). Factor 1 contained items reflecting concerns about birth and the baby, factor 2 concerns about physical symptoms and body image and factor 3 concerns about emotions and relationships. Conclusions: CFA confirmed that the three-factor model provided the best fit, with the items in each factor reflecting the findings of an earlier exploratory data analysis.

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“…When the adopted IRT model perfectly fits the analyzed data, the distribution of students' abilities will not affect the results of the item parameter estimation and vice versa [1,2]. Recently, owning to the advanced progress in information technology, the computerized adaptive test becomes more and more popular.…”

Section: Introductionmentioning

confidence: 99%

“…Item response theory (IRT) is with the features of parameter invariance and information function [1,2]. When the adopted IRT model perfectly fits the analyzed data, the distribution of students' abilities will not affect the results of the item parameter estimation and vice versa [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…For example, one of the six objectives for the longerterm development of Programme for International Student Assessment (PISA) is to continue exploiting the advantages of computer-based testing, including increasing the use of adaptive testing [3]. In IRT, student abilities are estimated according to students' response pattern and the adopted model, such as one or two or three-parameter logistic (1PL, 2PL, or 3PL) model [1,2].…”

Section: Introductionmentioning

confidence: 99%

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Item response theory with fuzzy markup language for parameter estimation and validation

Wang¹,

Wang²,

Lee³

et al. 2015

2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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Owing to advanced technical progress in information and communication technology, computerized adaptive assessment becomes more and more important for the personalized learning achievement. According to the response data from the conventional test and three-parameter logistic (3PL) model of the item response theory (IRT), this paper combines IRT with fuzzy markup language (FML) for an adaptive assessment application. The novel FML-based IRT estimation mechanism includes a Gauss-Seidel (GS) parameter estimation mechanism, a fuzzy knowledge base and a fuzzy rule base, to estimate the item parameters for each item. Meanwhile, it is able to infer the possibility of correct response to each item for each involved student. Additionally, this paper also proposes a static-IRT test assembly mechanism to assemble a form for the conventional test. After that, this paper chooses 5-fold cross validation to validate the research performance. From the experimental results, it shows that the proposed approach performs better than the traditional Bayesian estimation one.

show abstract

Item Response Theory

Cited by 1,512 publications

References 0 publications

Criteria for Selection and Evaluation of Scales and Measures

Criteria for Selection and Evaluation of Scales and Measures

The Prenatal Distress Questionnaire: an investigation of factor structure in a high risk population

Item response theory with fuzzy markup language for parameter estimation and validation

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