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Survey Item-Response Behavior as an Imperfect Proxy for Unobserved Ability: Theory and Application
, 2018 Sonja C. de New, Stefanie Schurer
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Investigating the Ordering Structure of Clustered Items Using Nonparametric Item Response Theory. [PDF]
Educ Psychol MeasKoopman L, Braeken J.
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Non-parametric item response theory applications in the assessment of dementia
, 2015 Sarah McGrory
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Annual Review of Statistics and Its Application, 2016
This review introduces classical item response theory (IRT) models as well as more contemporary extensions to the case of multilevel, multidimensional, and mixtures of discrete and continuous latent variables through the lens of discrete multivariate analysis.
Li Cai +3 more
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This review introduces classical item response theory (IRT) models as well as more contemporary extensions to the case of multilevel, multidimensional, and mixtures of discrete and continuous latent variables through the lens of discrete multivariate analysis.
Li Cai +3 more
openaire +2 more sources
The Counseling Psychologist, 1999
Item response theory (IRT) seeks to model the way in which latent psychological constructs manifest themselves in terms of observable item responses; this information is useful when developing, evaluating, and scoring tests. After providing an overview of the most popular IRT models (i.e., those applicable to dichotomously keyed items) and contrasting
Robert J. Harvey, Allen L. Hammer
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Item response theory (IRT) seeks to model the way in which latent psychological constructs manifest themselves in terms of observable item responses; this information is useful when developing, evaluating, and scoring tests. After providing an overview of the most popular IRT models (i.e., those applicable to dichotomously keyed items) and contrasting
Robert J. Harvey, Allen L. Hammer
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2011
Several user-contributed packages can fit IRT models. The packages we use the most is the ltm package by Dimitris Rizopoulos and the MCMCpack packages by Andrew Martin, Kevin Quinn, and Jong Hee Park. The eRm package by Patrick Mair, Reinhold Hatzinger, and Marco Maier also has powerful features. But our experience with eRm is limited at this time.
Yuelin Li, Jonathan Baron
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Several user-contributed packages can fit IRT models. The packages we use the most is the ltm package by Dimitris Rizopoulos and the MCMCpack packages by Andrew Martin, Kevin Quinn, and Jong Hee Park. The eRm package by Patrick Mair, Reinhold Hatzinger, and Marco Maier also has powerful features. But our experience with eRm is limited at this time.
Yuelin Li, Jonathan Baron
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2018
Item response theory (IRT) is a psychometric modeling framework for analyzing categorical data from questionnaires, tests, and other instruments that aim to measure underlying latent traits. Simply speaking, these models estimate a parameter for each item, as well as a parameter for each person.
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Item response theory (IRT) is a psychometric modeling framework for analyzing categorical data from questionnaires, tests, and other instruments that aim to measure underlying latent traits. Simply speaking, these models estimate a parameter for each item, as well as a parameter for each person.
+4 more sources
2014
Abstract Since the 1960s, there has been a revolution in the approach to scale development. Called item response theory (IRT), this approach challenges the notion that scales must be long in order to be reliable, and that psychometric properties of a scale derived from one group of people cannot be applied to different groups.
David L. Streiner +2 more
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Abstract Since the 1960s, there has been a revolution in the approach to scale development. Called item response theory (IRT), this approach challenges the notion that scales must be long in order to be reliable, and that psychometric properties of a scale derived from one group of people cannot be applied to different groups.
David L. Streiner +2 more
openaire +1 more source