Efficient nonparametric approaches for estimating the operating characteristics of discrete item responses

DOI10.1007/BF02294770zbMath0905.62115MaRDI QIDQ1265297

Fumiko Samejima

Publication date: 3 February 1999

Published in: Psychometrika (Search for Journal in Brave)

zbMATH Keywords

asymptotic normalitymaximum likelihood estimationbiaslatent trait modelsability estimationinformation functionsconstant information model

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Applications of statistics to psychology (62P15)

Related Items (5)

Departure from normal assumptions: A promise for future psychometrics with substantive mathematical modeling ⋮ Dimension in latent variable models. ⋮ Acceleration model in the heterogeneous case of the general graded response model ⋮ Logistic positive exponent family of models: virtue of asymmetric item characteristic curves ⋮ Graded response model based on the logistic positive exponent family of models for dichotomous responses

Cites Work

• Kernel smoothing approaches to nonparametric item characteristic curve estimation
• A method of estimating item characteristic functions using the maximum likelihood estimate of ability
• A comment on Birnbaum's three-parameter logistic model in the latent trait theory
• An approximation for the bias function of the maximum likelihood estimate of a latent variable for the general case where the item responses are discrete
• Systems of Frequency Curves
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

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