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 Nonparametric Bayesian Item Response Modeling Approach for Clustering Items and Individuals Simultaneously [PDF]
arXiv, 2020 Item response theory (IRT) is a popular modeling paradigm for measuring subject latent traits and item properties according to discrete responses in tests or questionnaires. There are very limited discussions on heterogeneity pattern detection for both items and individuals.
arxiv
Extended Rasch Modeling: The eRm Package for the Application of IRT Models in R [PDF]
Item response theory models (IRT) are increasingly becoming established in social science research, particularly in the analysis of performance or attitudinal data in psychology, education, medicine, marketing and other fields where testing is relevant ...
Patrick Mair, Reinhold Hatzinger
core +1 more source
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
Parameter Recovery with Marginal Maximum Likelihood and Markov Chain Monte Carlo Estimation for the Generalized Partial Credit Model [PDF]
arXiv, 2018 The generalized partial credit model (GPCM) is a popular polytomous IRT model that has been widely used in large-scale educational surveys and health care services. Same as other IRT models, GPCM can be estimated via marginal maximum likelihood estimation (MMLE) and Markov chain Monte Carlo (MCMC) methods.
arxiv
A Bayesian Nonparametric IRT Model [PDF]
arXiv, 2015 This paper introduces a flexible Bayesian nonparametric Item Response Theory (IRT) model, which applies to dichotomous or polytomous item responses, and which can apply to either unidimensional or multidimensional scaling. This is an infinite-mixture IRT model, with person ability and item difficulty parameters, and with a random intercept parameter ...
arxiv
An Introduction to the Special Volume on "Psychometrics in R'' [PDF]
This special volume presents a select number of psychometric techniques, many of them original, and their implementation in R packages.
Jan de Leeuw, Patrick Mair
core +1 more source
plink: An R Package for Linking Mixed-Format Tests Using IRT-Based Methods [PDF]
The R package plink has been developed to facilitate the linking of mixed-format tests for multiple groups under a common item design using unidimensional and multidimensional IRT-based methods.
Jonathan P. Weeks
core +1 more source
Polytomous Explanatory Item Response Models for Item Discrimination: Assessing Negative-Framing Effects in Social-Emotional Learning Surveys [PDF]
Modeling item parameters as a function of item characteristics has a long history but has generally focused on models for item location. Explanatory item response models for item discrimination are available but rarely used. In this study, we extend existing approaches for modeling item discrimination from dichotomous to polytomous item responses.
arxiv +1 more source
A new robust approach for the polytomous logistic regression model based on Rényi's pseudodistances [PDF]
arXivThis paper presents a robust alternative to the Maximum Likelihood Estimator (MLE) for the Polytomous Logistic Regression Model (PLRM), known as the family of minimum R\`enyi Pseudodistance (RP) estimators. The proposed minimum RP estimators are parametrized by a tuning parameter $\alpha\geq0$, and include the MLE as a special case when $\alpha=0 ...
arxiv