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Bayesian Item Response Modeling: Theory and Applications (Statistics for Social
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物品細節
- 物品狀況
- Book Title
- Bayesian Item Response Modeling: Theory and Applications
- Genre
- Research, Statistics, Testing & Measurement, Probability &
- Original Language
- English: Published; English: Original Language; English;
- Country/Region of Manufacture
- United States
- ISBN
- 9781441907417
- Subject Area
- Mathematics, Social Science
- Publication Name
- Bayesian Item Response Modeling : Theory and Applications
- Item Length
- 9.3 in
- Publisher
- Springer New York
- Subject
- Sociology / General, Probability & Statistics / General, General, Statistics, Probability & Statistics / Bayesian Analysis
- Publication Year
- 2010
- Series
- Statistics for Social and Behavioral Sciences Ser.
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Width
- 6.1 in
- Item Weight
- 49.4 Oz
- Number of Pages
- Xiv, 313 Pages
關於產品
Product Information
The modeling of item response data is governed by item response theory, also referred to as modern test theory. The eld of inquiry of item response theory has become very large and shows the enormous progress that has been made. The mainstream literature is focused on frequentist statistical methods for - timating model parameters and evaluating model t. However, the Bayesian methodology has shown great potential, particularly for making further - provements in the statistical modeling process. The Bayesian approach has two important features that make it attractive for modeling item response data. First, it enables the possibility of incorpor- ing nondata information beyond the observed responses into the analysis. The Bayesian methodology is also very clear about how additional information can be used. Second, the Bayesian approach comes with powerful simulation-based estimation methods. These methods make it possible to handle all kinds of priors and data-generating models. One of my motives for writing this book is to give an introduction to the Bayesian methodology for modeling and analyzing item response data. A Bayesian counterpart is presented to the many popular item response theory books (e.g., Baker and Kim 2004; De Boeck and Wilson, 2004; Hambleton and Swaminathan, 1985; van der Linden and Hambleton, 1997) that are mainly or completely focused on frequentist methods. The usefulness of the Bayesian methodology is illustrated by discussing and applying a range of Bayesian item response models.
Product Identifiers
Publisher
Springer New York
ISBN-10
1441907416
ISBN-13
9781441907417
eBay Product ID (ePID)
92316245
Product Key Features
Publication Name
Bayesian Item Response Modeling : Theory and Applications
Format
Hardcover
Language
English
Subject
Sociology / General, Probability & Statistics / General, General, Statistics, Probability & Statistics / Bayesian Analysis
Publication Year
2010
Series
Statistics for Social and Behavioral Sciences Ser.
Type
Textbook
Subject Area
Mathematics, Social Science
Number of Pages
Xiv, 313 Pages
Dimensions
Item Length
9.3 in
Item Width
6.1 in
Item Weight
49.4 Oz
Additional Product Features
Intended Audience
Scholarly & Professional
Number of Volumes
1 Vol.
Lc Classification Number
Hm511-538
Reviews
From the reviews: "Item response theory is a general paradigm for the design and analysis of questionnaires measuring abilities and attitudes of individuals. ... the book is written in a concise style and the technical level of the book is relatively high. ... I believe this book makes an important contribution in summarizing much of the important literature in Bayesian IRT and I think it will lead to future books focusing on the use and interpretation of these models from a practitioner's perspective." (Jim Albert, Journal of the American Statistical Association, Vol. 106 (495), September, 2011) "This book covers the parameter estimation of standard and extended IRT models using the Bayesian simulation based MCMC method. There are many Bayesian data analysis books, but this is the first book purely devoted to the Bayesian estimation of IRT models. ... Overall, it is a good book for advanced learners to grasp the theoretical and technical detail of Bayesian MCMC estimation of extended IRT models adapted to a specific measurement setting." (Hong Jiao, Psychometrika, Vol. 76 (2), April, 2011) "This book develops a comprehensive treatment of Bayesian item response modelling ... . The book is mostly self-contained. ... Each chapter ends with a section of carefully thought-out exercises covering both the mathematical aspects of the models and their application to the analysis of interesting real-life data. ... This book will equally cater for those users who just want to apply the models to analyze their data, and more technical users willing to get a deeper understanding of the models ... ." (Eduardo Gutirrez-Pea, International Statistical Review, Vol. 79 (3), 2011), From the reviews: "Item response theory is a general paradigm for the design and analysis of questionnaires measuring abilities and attitudes of individuals. ... the book is written in a concise style and the technical level of the book is relatively high. ... I believe this book makes an important contribution in summarizing much of the important literature in Bayesian IRT and I think it will lead to future books focusing on the use and interpretation of these models from a practitioner's perspective." (Jim Albert, Journal of the American Statistical Association, Vol. 106 (495), September, 2011) "This book covers the parameter estimation of standard and extended IRT models using the Bayesian simulation based MCMC method. There are many Bayesian data analysis books, but this is the first book purely devoted to the Bayesian estimation of IRT models. ... Overall, it is a good book for advanced learners to grasp the theoretical and technical detail of Bayesian MCMC estimation ofextended IRT models adapted to a specific measurement setting." (Hong Jiao, Psychometrika, Vol. 76 (2), April, 2011) "This book develops a comprehensive treatment of Bayesian item response modelling ... . The book is mostly self-contained. ... Each chapter ends with a section of carefully thought-out exercises covering both the mathematical aspects of the models and their application to the analysis of interesting real-life data. ... This book will equally cater for those users who just want to apply the models to analyze their data, and more technical users willing to get a deeper understanding of the models ... ." (Eduardo Guti é rrez-Pe ñ a, International Statistical Review, Vol. 79 (3), 2011), From the reviews: "Item response theory is a general paradigm for the design and analysis of questionnaires measuring abilities and attitudes of individuals. ... the book is written in a concise style and the technical level of the book is relatively high. ... I believe this book makes an important contribution in summarizing much of the important literature in Bayesian IRT and I think it will lead to future books focusing on the use and interpretation of these models from a practitioner's perspective." (Jim Albert, Journal of the American Statistical Association, Vol. 106 (495), September, 2011) "This book covers the parameter estimation of standard and extended IRT models using the Bayesian simulation based MCMC method. There are many Bayesian data analysis books, but this is the first book purely devoted to the Bayesian estimation of IRT models. ... Overall, it is a good book for advanced learners to grasp the theoretical and technical detail of Bayesian MCMC estimation of extended IRT models adapted to a specific measurement setting." (Hong Jiao, Psychometrika, Vol. 76 (2), April, 2011) "This book develops a comprehensive treatment of Bayesian item response modelling ... . The book is mostly self-contained. ... Each chapter ends with a section of carefully thought-out exercises covering both the mathematical aspects of the models and their application to the analysis of interesting real-life data. ... This book will equally cater for those users who just want to apply the models to analyze their data, and more technical users willing to get a deeper understanding of the models ... ." (Eduardo Guti é rrez-Pe ñ a, International Statistical Review, Vol. 79 (3), 2011), From the reviews: Item response theory is a general paradigm for the design and analysis of questionnaires measuring abilities and attitudes of individuals. … the book is written in a concise style and the technical level of the book is relatively high. … I believe this book makes an important contribution in summarizing much of the important literature in Bayesian IRT and I think it will lead to future books focusing on the use and interpretation of these models from a practitioner's perspective. (Jim Albert, Journal of the American Statistical Association, Vol. 106 (495), September, 2011) This book covers the parameter estimation of standard and extended IRT models using the Bayesian simulation based MCMC method. There are many Bayesian data analysis books, but this is the first book purely devoted to the Bayesian estimation of IRT models. … Overall, it is a good book for advanced learners to grasp the theoretical and technical detail of Bayesian MCMC estimation of extended IRT models adapted to a specific measurement setting. (Hong Jiao, Psychometrika, Vol. 76 (2), April, 2011) This book develops a comprehensive treatment of Bayesian item response modelling … . The book is mostly self-contained. … Each chapter ends with a section of carefully thought-out exercises covering both the mathematical aspects of the models and their application to the analysis of interesting real-life data. … This book will equally cater for those users who just want to apply the models to analyze their data, and more technical users willing to get a deeper understanding of the models … . (Eduardo Guti é rrez-Pe ñ a, International Statistical Review, Vol. 79 (3), 2011), From the reviews:Item response theory is a general paradigm for the design and analysis of questionnaires measuring abilities and attitudes of individuals. … the book is written in a concise style and the technical level of the book is relatively high. … I believe this book makes an important contribution in summarizing much of the important literature in Bayesian IRT and I think it will lead to future books focusing on the use and interpretation of these models from a practitioner's perspective. (Jim Albert, Journal of the American Statistical Association, Vol. 106 (495), September, 2011)This book covers the parameter estimation of standard and extended IRT models using the Bayesian simulation based MCMC method. There are many Bayesian data analysis books, but this is the first book purely devoted to the Bayesian estimation of IRT models. … Overall, it is a good book for advanced learners to grasp the theoretical and technical detail of Bayesian MCMC estimation of extended IRT models adapted to a specific measurement setting. (Hong Jiao, Psychometrika, Vol. 76 (2), April, 2011)This book develops a comprehensive treatment of Bayesian item response modelling … . The book is mostly self-contained. … Each chapter ends with a section of carefully thought-out exercises covering both the mathematical aspects of the models and their application to the analysis of interesting real-life data. … This book will equally cater for those users who just want to apply the models to analyze their data, and more technical users willing to get a deeper understanding of the models … . (Eduardo Gutiérrez-Peña, International Statistical Review, Vol. 79 (3), 2011)
Table of Content
to Bayesian Response Modeling.- Bayesian Hierarchical Response Modeling.- Basic Elements of Bayesian Statistics.- Estimation of Bayesian Item Response Models.- Assessment of Bayesian Item Response Models.- Multilevel Item Response Theory Models.- Random Item Effects Models.- Response Time Item Response Models.- Randomized Item Response Models.
Copyright Date
2010
Illustrated
Yes
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