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Bayesian Item Response Modeling by Jean Paul Fox (37 results)
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Bayesian Item Response Modeling
Published by Springer-Verlag New York Inc., 2010
ISBN 10: 1441907416 ISBN 13: 9781441907417
Language: English
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Bayesian Item Response Modeling: Theory and Applications (Statistics for Social and Behavioral Sciences)
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Bayesian Item Response Modeling: Theory and Applications (Statistics for Social and Behavioral Sciences)
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Bayesian Item Response Modeling : Theory and Applications
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Condition: New. pp. 328.
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Add to basketCondition: New. Introduces Bayesian item response modeling with examples in a wide array of contexts Gives a unified treatment of extending traditional item response models to handle more complex assessment data Computer code and examples facilitate the Baye.
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Bayesian Item Response Modeling
Published by Springer-Verlag New York Inc., US, 2010
ISBN 10: 1441907416 ISBN 13: 9781441907417
Language: English
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Bayesian Item Response Modeling
Published by Springer New York, Springer US Sep 2012, 2012
ISBN 10: 1461426065 ISBN 13: 9781461426066
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 328 pp. Englisch.
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Bayesian Item Response Modeling : Theory and Applications
Published by Springer New York, Springer US, 2012
ISBN 10: 1461426065 ISBN 13: 9781461426066
Language: English
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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Bayesian Item Response Modeling : Theory and Applications
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Bayesian Item Response Modeling (Statistics for Social and Behavioral Sciences)
Published by Springer-Verlag New York Inc., 2012
ISBN 10: 1461426065 ISBN 13: 9781461426066
Language: English
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Add to basketPaperback. Condition: Brand New. 327 pages. 9.20x6.10x0.79 inches. In Stock.
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Bayesian Item Response Modeling
Published by Springer-Verlag New York Inc., US, 2010
ISBN 10: 1441907416 ISBN 13: 9781441907417
Language: English
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Add to basketHardback. Condition: New. 2010 ed. 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.
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Bayesian Item Response Modeling: Theory and Applications
Published by Springer-Verlag New York Inc., 2012
ISBN 10: 1461426065 ISBN 13: 9781461426066
Language: English
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 527.
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Bayesian Item Response Modeling: Theory and Applications
Published by Springer-Verlag New York Inc., 2010
ISBN 10: 1441907416 ISBN 13: 9781441907417
Language: English
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Bayesian Item Response Modeling
Published by Springer New York Jun 2010, 2010
ISBN 10: 1441907416 ISBN 13: 9781441907417
Language: English
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Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 313 pp. Englisch.
