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Generalized estimating equations for longitudinal mixed Rasch model
Journal of Statistical Planning and Inference, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Feddag, Mohand L., Mesbah, Mounir
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Mixed Rasch Modeling of the Self-Rating Depression Scale
Educational and Psychological Measurement, 2007In this study, mixed Rasch modeling was used on the Self-Rating Depression Scale (SDS), a widely used measure of depression, among a non-Western sample of 618 Korean college students. The results revealed three latent classes and confirmed the unidimensionality of the SDS.
Sehee Hong, Sae-Young Min
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Goodness of Fit Test and Latent Distribution Estimation in the Mixed Rasch Model
Communications in Statistics - Theory and Methods, 2006The Cramer-von Mises test methodology is applied to build a goodness-of fit test for the mixed Rasch model. The Mixed Rasch Model is a probability model of a multivariate discrete random variable driven by an unknown latent continuous variable. The problem of estimation of the unknown fixed difficulty parameters and the latent density function is also ...
G. Martynov, M. Mesbah
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Sequential Analysis of Quality-of-Life Measurements Using Mixed Rasch Models
2008Early stopping of clinical trials in the case of either beneficial or deleterious effect of a treatment on quality of life (QoL) is an important issue. QoL is usually evaluated using self-assessment questionnaires and responses to the items are usually combined into QoL scores assumed to be normally distributed.
Véronique Sébille +2 more
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Parameter recovery and model selection in mixed Rasch models
British Journal of Mathematical and Statistical Psychology, 2011This study examines the precision of conditional maximum likelihood estimates and the quality of model selection methods based on information criteria (AIC and BIC) in mixed Rasch models. The design of the Monte Carlo simulation study included four test lengths (10, 15, 25, 40), three sample sizes (500, 1000, 2500), two simulated mixture conditions ...
Preinerstorfer, David, Formann, Anton K
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Pairwise likelihood for the longitudinal mixed Rasch model
Computational Statistics & Data Analysis, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Feddag M., Bacci S.
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A Mixed Rasch Model of Dual-Process Conditional Reasoning
Quarterly Journal of Experimental Psychology, 2008A 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 +3 more
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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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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
2004The 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
2019The 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 +3 more
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