Multidimensional item response theory:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Melbourne
SAGE
[2020]
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| Series: | Quantitative applications in the social sciences
183 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xiii, 138 Seiten Diagramme |
| ISBN: | 9781506384252 |
Staff View
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Record in the Search Index
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| adam_text | CONTENTS Series Editor’s Introduction ix Acknowledgments xi About the Author xiii Chapter 1: Introduction 1 Chapter 2: Unidimensional Item Response Theory 5 What Is a Latent Trait? Assumptions of UIRT UIRT Models for Dichotomous Data R Code UIRT Models for Polytomous Data Additional UIRT Models R Code UIRT Estimation Other Estimation Methods R Code Chapter 3: MIRT Models for Dichotomous Data Compensation in MIRT Modeling Compensatory MIRT Models R Code Partially Compensatory MIRT Models R Code Additional MIRT Models for Dichotomous Data R Code Recent Advances in Dichotomous MIRT Modeling Chapter 4: MIRT Models for Polytomous Data R Code Additional Polytomous MIRT Models 5 5 6 13 13 17 17 17 26 26 27 27 31 37 38 41 41 45 45 47 54 54 Chapter 5: Descriptive MIRT Statistics 55 The Θ-Space The Item Response Surface Conditional Response Functions The Direction of Measurement 55 57 58 60
Person Parameters in MIRT MIRT Information Polytomous MIRT Descriptives Test-Level MIRT Descriptives 67 70 71 75 Chapter 6: Item Factor Structures Two-Tier Model Correlated-Traits Model Bifactor Model Testlet Response Model R Code 77 77 80 81 81 82 Chapter 7: Estimation in MIRT Models Conceptual Illustration Missing Data Formulation Two Challenges Adaptive Quadrature Bayesian Estimation MH-RM Estimation R Code 83 83 84 87 88 89 90 91 Chapter 8: MIRT Model Diagnostics and Evaluation Dimensionality Assessment Test-Level Fit Assessment Item-Level F it Assessment Model Comparison Methods 93 93 97 100 103 Chapter 9: MIRT Applications Linking and Equating R Code Differential Item Functioning R Code Computerized Adaptive Testing R Code Applications of the Two-Tier Item Factor Structure Further MIRT Applications 105 105 107 107 109 109 111 111 113 References 115 Index 133
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| adam_txt |
CONTENTS Series Editor’s Introduction ix Acknowledgments xi About the Author xiii Chapter 1: Introduction 1 Chapter 2: Unidimensional Item Response Theory 5 What Is a Latent Trait? Assumptions of UIRT UIRT Models for Dichotomous Data R Code UIRT Models for Polytomous Data Additional UIRT Models R Code UIRT Estimation Other Estimation Methods R Code Chapter 3: MIRT Models for Dichotomous Data Compensation in MIRT Modeling Compensatory MIRT Models R Code Partially Compensatory MIRT Models R Code Additional MIRT Models for Dichotomous Data R Code Recent Advances in Dichotomous MIRT Modeling Chapter 4: MIRT Models for Polytomous Data R Code Additional Polytomous MIRT Models 5 5 6 13 13 17 17 17 26 26 27 27 31 37 38 41 41 45 45 47 54 54 Chapter 5: Descriptive MIRT Statistics 55 The Θ-Space The Item Response Surface Conditional Response Functions The Direction of Measurement 55 57 58 60
Person Parameters in MIRT MIRT Information Polytomous MIRT Descriptives Test-Level MIRT Descriptives 67 70 71 75 Chapter 6: Item Factor Structures Two-Tier Model Correlated-Traits Model Bifactor Model Testlet Response Model R Code 77 77 80 81 81 82 Chapter 7: Estimation in MIRT Models Conceptual Illustration Missing Data Formulation Two Challenges Adaptive Quadrature Bayesian Estimation MH-RM Estimation R Code 83 83 84 87 88 89 90 91 Chapter 8: MIRT Model Diagnostics and Evaluation Dimensionality Assessment Test-Level Fit Assessment Item-Level F it Assessment Model Comparison Methods 93 93 97 100 103 Chapter 9: MIRT Applications Linking and Equating R Code Differential Item Functioning R Code Computerized Adaptive Testing R Code Applications of the Two-Tier Item Factor Structure Further MIRT Applications 105 105 107 107 109 109 111 111 113 References 115 Index 133 |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T14:20:18Z |
| indexdate | 2024-07-10T08:50:43Z |
| institution | BVB |
| isbn | 9781506384252 |
| language | English |
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| physical | xiii, 138 Seiten Diagramme |
| publishDate | 2020 |
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| spelling | Bonifay, Wes 1982- Verfasser (DE-588)1211498115 aut Multidimensional item response theory Wes Bonifay, University of Missouri Los Angeles ; London ; New Delhi ; Singapore ; Washington DC ; Melbourne SAGE [2020] © 2020 xiii, 138 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Quantitative applications in the social sciences 183 Probabilistische Testtheorie (DE-588)4496586-2 gnd rswk-swf Probabilistische Testtheorie (DE-588)4496586-2 s DE-604 Quantitative applications in the social sciences 183 (DE-604)BV000005102 183 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032077776&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bonifay, Wes 1982- Multidimensional item response theory Quantitative applications in the social sciences Probabilistische Testtheorie (DE-588)4496586-2 gnd |
| subject_GND | (DE-588)4496586-2 |
| title | Multidimensional item response theory |
| title_auth | Multidimensional item response theory |
| title_exact_search | Multidimensional item response theory |
| title_exact_search_txtP | Multidimensional item response theory |
| title_full | Multidimensional item response theory Wes Bonifay, University of Missouri |
| title_fullStr | Multidimensional item response theory Wes Bonifay, University of Missouri |
| title_full_unstemmed | Multidimensional item response theory Wes Bonifay, University of Missouri |
| title_short | Multidimensional item response theory |
| title_sort | multidimensional item response theory |
| topic | Probabilistische Testtheorie (DE-588)4496586-2 gnd |
| topic_facet | Probabilistische Testtheorie |
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