Item Response Theory - Info and Reading Options
Parameter Estimation Techniques, Second Edition
By Frank B. Baker
"Item Response Theory" was published by Taylor & Francis Group in 2004 - Boca Raton, it has 528 pages and the language of the book is English.
“Item Response Theory” Metadata:
- Title: Item Response Theory
- Author: Frank B. Baker
- Language: English
- Number of Pages: 528
- Publisher: Taylor & Francis Group
- Publish Date: 2004
- Publish Location: Boca Raton
“Item Response Theory” Subjects and Themes:
- Subjects: ➤ Parameter estimation - Item response theory - Estimation d'un paramètre - MATHEMATICS - Applied - Probability & Statistics - General - Mathematical Computing - Statistics as Topic - Psychometrics - Itemresponsietheorie
Edition Identifiers:
- The Open Library ID: OL33504140M - OL4275818W
- ISBN-13: 9781482276725
- All ISBNs: 9781482276725
AI-generated Review of “Item Response Theory”:
"Item Response Theory" Description:
Open Data:
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Preface to the Second Edition -- References -- Preface to the First Edition -- References -- Contents -- 1. The Item Characteristic Curve: Dichotomous Response -- 1.1 Introduction -- 1.2 The Item Characteristic Curve -- 1.3 Two Item Characteristic Curve Models -- 1.3.1 The Normal Ogive Model -- 1.3.2 The Logistic Ogive Model -- 1.4 Extension of the Item Characteristic Curve Models: Dichotomous Scoring -- 1.4.1 Birnbaum's Three-paralneter Model -- 1.4.2 The One-parameter Logistic Model-The Rasch Model -- 1.5 Summary -- 2. Estimating the Parameters of an Item Characteristic Curve -- 2.1 Introduction -- 2.2 Maximum Likelihood Estimation: Normal Ogive Model -- 2.3 Maximum Likelihood Estimation: Logistic Model -- 2.4 Influence of the Weighting Coefficients -- 2.5 The Item Log-Likelihood Surface -- 2.6 Maximum Likelihood Estimation: Three-Parameter Model -- 2.7 Minimum X2 and Minimum Transform X2 Estimations -- 2.7.1 Minimum X2 Estimation -- 2.7.2 Minimum Transform X2 Estimation -- 2.8 Summary -- 3. Maximum Likelihood Estimation of Examinee Ability -- 3.1 Introduction -- 3.2 Maximum Likelihood Estimation of Ability -- 3.2.1 Normal Model -- 3.2.2 Logistic Model -- 3.2.3 Birnbaum's Three-Parameter (Logistic) Model -- 3.3 Information Functions -- 3.3.1 Item Information Function -- 3.3.2 Samejima's Approach to the Item Information Function -- 3.3.3 Test Information Function -- 3.4 Summary -- 4. Procedures for Estimating Both Ability and Item Parameters. -- 4.1 Introduction -- 4.2 Joint Maximum Likelihood Estimation: The Birnbaum Paradigm -- 4.2.1 Some Additional Facets of the Birnbaum Paradigm -- 4.2.2 Quality of the Parameter Estimates -- 4.3 Summary -- 5. The Rasch Model -- 5.1 Introduction -- 5.2 The Rasch Model -- 5.3 Separation of Parameters -- 5.4 Specific Objectivity
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