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Nonparametric extension of item response theory models and its usefulness for assessment of dimensionality of motor tests [Neparametrické rozšíření IRT modelů: užitečnost pro určování dimenzionality motorických testů]
Jan Štochl
Language English Country Czech Republic
- MeSH
- Lower Extremity physiopathology MeSH
- Adult MeSH
- Financing, Organized MeSH
- Upper Extremity physiopathology MeSH
- Hypokinesia physiopathology MeSH
- Humans MeSH
- Parkinson Disease diagnosis physiopathology MeSH
- Parkinsonian Disorders physiopathology MeSH
- Speech Disorders physiopathology MeSH
- Posture physiology MeSH
- Statistics as Topic MeSH
- Muscle Rigidity physiopathology MeSH
- Models, Theoretical MeSH
- Tremor physiopathology MeSH
- Facial Expression MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
The nonparametric extension of the well known item response theory (IRT) models will be presented for dichotomous and polytomous items. In addition two types of nonparametric IRT models (Mokken´s monotone homogeneity model and Mokken´s double monotonicity model) will be introduced. It will be shown that nonparametric approach can provide useful information about the dimensionality and reliability of the scales and (motor) test batteries relaxing some of the strong assumptions which underlie the standard parametric IRT models. Numerical example based on real data is presented for illustration.
Neparametrické rozšíření IRT modelů: užitečnost pro určování dimenzionality motorických testů
Lit.: 36
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- $a Neparametrické rozšíření IRT modelů: užitečnost pro určování dimenzionality motorických testů
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- $a Charles University, Faculty of Physical Education and Sport, Prague
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- $a The nonparametric extension of the well known item response theory (IRT) models will be presented for dichotomous and polytomous items. In addition two types of nonparametric IRT models (Mokken´s monotone homogeneity model and Mokken´s double monotonicity model) will be introduced. It will be shown that nonparametric approach can provide useful information about the dimensionality and reliability of the scales and (motor) test batteries relaxing some of the strong assumptions which underlie the standard parametric IRT models. Numerical example based on real data is presented for illustration.
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