Rasch-based high-dimensionality data reduction and class prediction with applications to microarray gene expression data [PDF]
Expert Systems with Applications, 2010;37(7):5178-5185, 2010 Class prediction is an important application of microarray gene expression data analysis. The high-dimensionality of microarray data, where number of genes (variables) is very large compared to the number of samples (obser- vations), makes the application of many prediction techniques (e.g., logistic regression, discriminant analysis) difficult.
arxiv +1 more source
A Spectral Approach to Item Response Theory [PDF]
arXiv, 2022 The Rasch model is one of the most fundamental models in \emph{item response theory} and has wide-ranging applications from education testing to recommendation systems. In a universe with $n$ users and $m$ items, the Rasch model assumes that the binary response $X_{li} \in \{0,1\}$ of a user $l$ with parameter $\theta^*_l$ to an item $i$ with parameter
arxiv
Strong Gaussian approximation of the mixture Rasch model [PDF]
arXiv, 2016 We consider the famous Rasch model, which is applied to psychometric surveys when n persons under test answer m questions. The score is given by a realization of a random binary (n,m)-matrix. Its (j,k)th component indicates whether or not the answer of the jth person to the kth question is correct.
arxiv
A multidimensional latent class Rasch model for the assessment of the Health-related Quality of Life [PDF]
arXiv, 2012 The work describes a multidimensional latent class Rasch model and its application to data about the measurement of some aspects of Health-related Quality of Life and Anxiety and Depression in oncological patients.
arxiv
Assessment of school performance through a multilevel latent Markov Rasch model [PDF]
, 2009 An extension of the latent Markov Rasch model is described for the analysis of binary longitudinal data with covariates when subjects are collected in clusters, e.g. students clustered in classes. For each subject, the latent process is used to represent the characteristic of interest (e.g.
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Dependent Dirichlet Process Rating Model (DDP-RM) [PDF]
arXiv, 2012 Typical IRT rating-scale models assume that the rating category threshold parameters are the same over examinees. However, it can be argued that many rating data sets violate this assumption. To address this practical psychometric problem, we introduce a novel, Bayesian nonparametric IRT model for rating scale items. The model is an infinite-mixture of
arxiv
TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs [PDF]
arXiv, 2016 This paper explores the suitability of using automatically discovered topics from MOOC discussion forums for modelling students' academic abilities. The Rasch model from psychometrics is a popular generative probabilistic model that relates latent student skill, latent item difficulty, and observed student-item responses within a principled, unified ...
arxiv
An Estimation and Analysis Framework for the Rasch Model [PDF]
arXiv, 2018 The Rasch model is widely used for item response analysis in applications ranging from recommender systems to psychology, education, and finance. While a number of estimators have been proposed for the Rasch model over the last decades, the available analytical performance guarantees are mostly asymptotic. This paper provides a framework that relies on
arxiv
The Q-Matrix Anchored Mixture Rasch Model. [PDF]
Front Psychol, 2021 Tseng MC, Wang WC.
europepmc +1 more source
Setting a standard for low reading proficiency: A comparison of the bookmark procedure and constrained mixture Rasch model. [PDF]
PLoS One, 2021 Feseker T, Gnambs T, Artelt C.
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