Results 181 to 190 of about 4,160 (221)

Pairwise likelihood for the longitudinal mixed Rasch model

Computational Statistics & Data Analysis, 2009
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Feddag M., Bacci S.
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A Mixed Rasch Model of Dual-Process Conditional Reasoning

Quarterly Journal of Experimental Psychology, 2008
A fine-grained dual-process approach to conditional reasoning is advocated: Responses to conditional syllogisms are reached through the operation of either one of two systems, each of which can rely on two different mechanisms. System1 relies either on pragmatic implicatures or on the retrieval of information from semantic memory; System2 operates ...
Jean-François, Bonnefon, Michael, Eid, Stéphane, Vautier, Saïd, Jmel   +3 more
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Identification of parametric Rasch-type models

Journal of Statistical Planning and Inference, 2013
In modern Item Response Theory, the Rasch model is viewed as a Generalized Linear Mixed Model, where the item parameters correspond to the fixed-effects, whereas the person specific parameters are the random-effects. The statistical model, bearing on the
Ernesto San Martín, Jean-Marie Rolin
exaly   +2 more sources

Polytomous Mixed Rasch Models

1995
In this chapter, the discrete mixture distribution framework is developed for Rasch models for items with a polytomous ordered response format. Four of these models will be considered, based on different restrictions regarding the so-called threshold distances (Section 20.2).
Matthias von Davier, Jürgen Rost
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Semiparametric Approach to the Multivariate Mixed Rasch Model

2004
The multivariate mixed Rasch model is used to analyse binary reponses of questionnaires with several subscales. The responses of our model are two-way correlated. First, at a given subscale of questionnaire, the binary responses of a single individual are correlated: second, they are repeated over the subscales and also become correlated.
Mohand-Larbi Feddag, Mounir Mesbah
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Applying the mixed Rasch model in assessing reading comprehension

2019
The mixed Rasch model (MRM) is an extension of the standard Rasch model, which identifies latent classes of respondents for whom differential item functioning (DIF) exists. MRM helps in detecting qualitative differences among test takers and in finding out how individual differences affect test performance by decomposing the population into meaningful ...
Purya Baghaei, Christoph J. Kemper, Monique Reichert, Samuel Greiff   +3 more
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Mixed model estimation methods for the Rasch model.

Journal of applied measurement, 2005
Mixed models take the dependency between observations based on the same person into account by introducing one or more random effects. After introducing the mixed model framework, it is explained, by taking the Rasch model as a generic example, how item response models can be conceptualized as generalized linear and nonlinear mixed models.
Frank, Rijmen, Francis, Tuerlinckx, Michel, Meulders, Dirk J M, Smits, Katalin, Balázs   +4 more
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Pairwise- and marginal-likelihood estimation for the mixed Rasch model with binary data

Journal of Statistical Computation and Simulation, 2011
A marginal–pairwise-likelihood estimation approach is examined in the mixed Rasch model with the binary response and logit link. This method belonging to the broad class of composite likelihood provides estimators with desirable asymptotic properties such as consistency and asymptotic normality. We study the performance of the proposed methodology when
M.-L. Feddag, J.-B. Hardouin, V. Sebille
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The dimensional assessment of personality in drug addicts: a mixed-effects Rasch model approach

Quality & Quantity, 2013
Drug abuse results from a series of different factors, such as social and family issues. Subjects more vulnerable to develop an addiction are, for instance, people living in high-stress environments who may resort to addiction in order to cope with their circumstances, such as demanding jobs, family crisis or other situations or people living in low ...
SARRA A., FONTANELLA, Lara, D'EGIDIO F., FRATTONE P.   +3 more
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Mixed Rasch Models for Measurement in Cognitive Psychology

2007
To apply standard unidimensional IRT models to ability measurement, it must be assumed that individuals at the same level of performance are in fact comparable. That is, individuals with the same estimate on the latent trait are interchangeable and thus can have identical interpretations given to their scores. Such interpretations, of course, depend on
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