Item response theory with estimation of the latent population distribution using spline-based densities

DOI10.1007/s11336-004-1175-8zbMath1306.62517OpenAlexW2083665827WikidataQ89276375 ScholiaQ89276375MaRDI QIDQ2261025

David Thissen, Carol M. Woods

Publication date: 6 March 2015

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-004-1175-8

zbMATH Keywords

splinesitem response theorydensity estimationlatent variablepopulation distributionmarginal maximum likelihood

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Related Items (14)

A deep learning algorithm for high-dimensional exploratory item factor analysis ⋮ Modeling and testing differential item functioning in unidimensional binary item response models with a single continuous covariate: a functional data analysis approach ⋮ Maximum marginal likelihood estimation of a monotonic polynomial generalized partial credit model with applications to multiple group analysis ⋮ Identification of the 1PL model with guessing parameter: parametric and semi-parametric results ⋮ Standard error of ability estimates and the classification accuracy and consistency of binary decisions ⋮ A two-tier full-information item factor analysis model with applications ⋮ Estimation of generalized linear latent variable models via fully exponential Laplace approximation ⋮ Information matrices and standard errors for MLEs of item parameters in IRT ⋮ Asymptotic robustness study of the polychoric correlation estimation ⋮ Latent variable models for ordinal data by using the adaptive quadrature approximation ⋮ On the Bayesian nonparametric generalization of IRT-type models ⋮ Bootstrap-calibrated interval estimates for latent variable scores in item response theory ⋮ Matching IRT models to patient-reported outcomes constructs: the graded response and log-logistic models for scaling depression ⋮ Optimal scores: an alternative to parametric item response theory and sum scores

Uses Software

• BILOG

Cites Work

• Unnamed Item
• Prediction functions for categorical panel data
• Dispersion of Categorical Variables and Penalty Functions: Derivation, Estimation, and Comparability
• On estimating binomial response relations
• On Deviations of the Sample Mean
• Analysis of Dispersion of Multinomial Responses
• 21 Assessing the Fit of Item Response Theory Models
• Elicitation of Personal Probabilities and Expectations
• A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations
• Measures of Association for Cross Classifications
• The Expected Value and Variance of the Reciprocal and Other Negative Powers of a Positive Bernoullian Variate

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