Asymptotic expansions for the pivots using log-likelihood derivatives with an application in item response theory

DOI10.1016/j.jmva.2010.04.001zbMath1201.62025OpenAlexW2047869051MaRDI QIDQ990897

Haruhiko Ogasawara

Publication date: 1 September 2010

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2010.04.001

zbMATH Keywords

item response theorysandwich estimatorpivotsinverse expansionlog-likelihood derivatives

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Applications of statistics to psychology (62P15)

Related Items (max. 100)

Asymptotic expansions for the estimators of Lagrange multipliers and associated parameters by the maximum likelihood and weighted score methods ⋮ Bias Adjustment Minimizing the Asymptotic Mean Square Error ⋮ Asymptotic cumulants of the minimum phi-divergence estimator for categorical data under possible model misspecification ⋮ Asymptotic cumulants of ability estimators using fallible item parameters ⋮ Asymptotic cumulants of the estimator of the canonical parameter in the exponential family ⋮ Cornish-Fisher expansions using sample cumulants and monotonic transformations ⋮ Information matrices and standard errors for MLEs of item parameters in IRT ⋮ A unified treatment of agreement coefficients and their asymptotic results: the formula of the weighted mean of weighted ratios ⋮ Optimal information criteria minimizing their asymptotic mean square errors ⋮ Asymptotic properties of the Bayes modal estimators of item parameters in item response theory ⋮ Asymptotic expansions for the ability estimator in item response theory

Uses Software

• bootstrap

Cites Work

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• Asymptotic cumulants of the parameters estimators in item response theory
• Edgeworth corrected pivotal statistics and the bootstrap
• The likelihood ratio criterion and the asymptotic expansion of its distribution
• On second-order optimality of the observed Fisher information
• Asymptotic standard errors of IRT observed-score equating methods
• A GENERAL METHOD FOR APPROXIMATING TO THE DISTRIBUTION OF LIKELIHOOD RATIO CRITERIA
• Some Properties of the Pivotal Statistic Based on the Asymptotically Distribution-Free Theory in Structural Equation Modeling
• Better Bootstrap Confidence Intervals
• Prepivoting Test Statistics: A Bootstrap View of Asymptotic Refinements
• Nonparametric standard errors and confidence intervals
• Asymptotic properties of a conditional maximum‐likelihood estimator
• Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
• Higher‐order asymptotics under model misspecification
• 15 Item Response Theory in a General Framework
• APPROXIMATE CONFIDENCE INTERVALS
• APPROXIMATE CONFIDENCE INTERVALS
• The bootstrap and Edgeworth expansion

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