Results 21 to 30 of about 1,357,661 (125)
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Incorporating Item Response Theory (IRT) into NLP tasks can provide valuable information about model performance and behavior. Traditionally, IRT models are learned using human response pattern (RP) data, presenting a significant bottleneck for large ...
John P. Lalor, Hao Wu, Hong Yu
semanticscholar +1 more source
Multivariate Behavioral Research, 2018 In recent years, network models have been proposed as an alternative representation of psychometric constructs such as depression. In such models, the covariance between observables (e.g., symptoms like depressed mood, feelings of worthlessness, and ...
M. Marsman +7 more
semanticscholar +1 more source
Assessing Personality Traits Through Response Latencies Using Item Response Theory [PDF]
, 2011 Recent studies have revealed a relation between the given response and the response latency for personality questionnaire items in the form of an inverted-U effect, which has been interpreted in light of schema-driven behavior.
Ortner, Tuulia M., Ranger, Jochen
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BUGS Code for Item Response Theory [PDF]
, 2010 I present BUGS code to fit common models from item response theory (IRT), such as the two parameter logistic model, three parameter logisitic model, graded response model, generalized partial credit model, testlet model, and generalized testlet models. I
Curtis, S. McKay
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Reliability estimation for single dichotomous items based on Mokken's IRT model [PDF]
, 1995 Item reliability is of special interest for Mokken’s nonparametric item response theory, and is useful for the evaluation of item quality in nonparametric test construction research. It is also of interest for nonparametric person-fit analysis.
Meijer, Rob R. +2 more
core +4 more sources
Calculating the random guess scores of multiple-response and matching test items [PDF]
, 2018 For achievement tests, the guess score is often used as a baseline for the lowest possible grade for score to grade transformations and setting the cut scores.
GA Brown +12 more
core +2 more sources
Journal of Patient-Reported Outcomes, 2019 BackgroundThis paper is part of a series comparing different psychometric approaches to evaluate patient-reported outcome (PRO) measures using the same items and dataset.
A. Stover +4 more
semanticscholar +1 more source
Item Response Modeling of Multivariate Count Data With Zero Inflation, Maximum Inflation, and Heaping [PDF]
, 2017 Questionnaires that include items eliciting count responses are becoming increasingly common in psychology. This study proposes methodological techniques to overcome some of the challenges associated with analyzing multivariate item response data that ...
Brooke E. Magnus +5 more
core +2 more sources
Advances in applications of item response theory to clinical assessment.
Psychological Assessment, 2019 Item response theory (IRT) is moving to the forefront of methodologies used to develop, evaluate, and score clinical measures. Funding agencies and test developers are routinely supporting IRT work, and the theory has become closely tied to technological
M. Thomas
semanticscholar +1 more source
Multidimensional item response theory and the Force Concept Inventory [PDF]
Physical Review Physics Education Research, 2018 Research on the test structure of the Force Concept Inventory (FCI) has largely been performed with exploratory methods such as factor analysis and cluster analysis.
J. Stewart +3 more
semanticscholar +1 more source