The theory and practice of item response theory:

Cover -- Half Title Page -- Series Page -- Title Page -- Copyright -- Dedication -- Series Editor's Note -- Preface -- Contents -- Symbols and Acronyms -- 1. Introduction to Measurement -- Measurement -- Some Measurement Issues -- Item Response Theory -- Classical Test Theory -- Latent Class An...

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Bibliographische Detailangaben
1. Verfasser: De Ayala, Rafael J. 1957- (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: New York ; London The Guilford Press [2022]
Ausgabe:Second edition
Schriftenreihe:Methodology in the social sciences
Schlagworte:
Online-Zugang:UBA01
Zusammenfassung:Cover -- Half Title Page -- Series Page -- Title Page -- Copyright -- Dedication -- Series Editor's Note -- Preface -- Contents -- Symbols and Acronyms -- 1. Introduction to Measurement -- Measurement -- Some Measurement Issues -- Item Response Theory -- Classical Test Theory -- Latent Class Analysis -- Summary -- 2. The One-Parameter Model -- Conceptual Development of the Rasch Model -- The One-Parameter Model -- The One-Parameter Logistic Model and the Rasch Model -- Assumptions Underlying the Model -- An Empirical Data Set: The Mathematics Data Set -- Conceptually Estimating an Individual's Location -- Some Pragmatic Characteristics of Maximum Likelihood Estimates -- The Standard Error of Estimate and Information -- An Instrument's Estimation Capacity -- Summary -- 3. Joint Maximum Likelihood Parameter Estimation -- Joint Maximum Likelihood Estimation -- Indeterminacy of Parameter Estimates -- How Large a Calibration Sample? -- Example: Application of the Rasch Model to the Mathematics Data, JMLE, BIGSTEPS -- Example: Application of the Rasch Model to the Mathematics Data, JMLE, mixRasch -- Validity Evidence -- Summary of the Application of the Rasch Model -- Summary -- 4. Marginal Maximum Likelihood Parameter Estimation -- Marginal Maximum Likelihood Estimation -- Estimating an Individual's Location: Expected A Posteriori -- Example: Application of the Rasch Model to the Mathematics Data, MMLE, BILOG-MG -- Metric Transformation and the Total Characteristic Function -- Example: Application of the Rasch Model to the Mathematics Data, MMLE, mirt -- Summary -- 5. The Two-Parameter Model -- Conceptual Development of the Two-Parameter Model -- Information for the Two-Parameter Model -- Conceptual Parameter Estimation for the 2PL Model -- How Large a Calibration Sample? -- Metric Transformation, 2PL Model.
Beschreibung:1 Online-Ressource (xxiv, 643 Seiten) Diagramme
ISBN:9781462547944

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