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02559nam a22004455i 4500 |
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100301s1999 xxu| s |||| 0|eng d |
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|a 9780387227023
|9 978-0-387-22702-3
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|a 10.1007/b98832
|2 doi
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|a QA276-280
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|a SOC027000
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|a 519.5
|2 23
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|a Johnson, Valen E.
|e author.
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|a Ordinal Data Modeling
|h [electronic resource] /
|c by Valen E. Johnson, James H. Albert.
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|a New York, NY :
|b Springer New York,
|c 1999.
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|a X, 258 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|2 rdamedia
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|a online resource
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|a text file
|b PDF
|2 rda
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|a Statistics for Social Science and Behavorial Sciences
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|a Review of Classical and Bayesian Inference -- Review of Bayesian Computation -- Regression Models for Binary Data -- Regression Models for Ordinal Data -- Analyzing Data from Multiple Raters -- Item Response Modeling -- Graded Response Models: A Case Study of Undergraduate Grade Data.
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|a Ordinal Data Modeling is a comprehensive treatment of ordinal data models from both likelihood and Bayesian perspectives. Written for graduate students and researchers in the statistical and social sciences, this book describes a coherent framework for understanding binary and ordinal regression models, item response models, graded response models, and ROC analyses, and for exposing the close connection between these models. A unique feature of this text is its emphasis on applications. All models developed in the book are motivated by real datasets, and considerable attention is devoted to the description of diagnostic plots and residual analyses. Software and datasets used for all analyses described in the text are available on websites listed in the preface.
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|a Statistics.
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|a Statistics.
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|a Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
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|a Albert, James H.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9780387987187
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|a Statistics for Social Science and Behavorial Sciences
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|u http://dx.doi.org/10.1007/b98832
|z Full Text via HEAL-Link
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|a ZDB-2-SMA
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|a ZDB-2-BAE
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|a Mathematics and Statistics (Springer-11649)
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