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Categorical Data Analysis Multilevel by Liu Xing (16 results)
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Condition: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
First Edition
paperback. Condition: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Condition: As New. Unread book in perfect condition.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Condition: New.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Categorical Data Analysis and Multilevel Modeling Using R (Paperback)
Language: English
Published by SAGE Publications Inc, Thousand Oaks, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Paperback. Condition: new. Paperback. Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. It offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: New.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Condition: New.
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Paperback. Condition: Brand New. 708 pages. 8.75x7.25x1.25 inches. In Stock.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Categorical Data Analysis and Multilevel Modeling Using R (Paperback)
Language: English
Published by SAGE Publications Inc, Thousand Oaks, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Paperback. Condition: new. Paperback. Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. It offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by SAGE Publications Inc Mai 2022, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal,and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site. 744 pp. Englisch.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by Sage Publications|SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. It offers a unified framework for b.
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Categorical Data Analysis and Multilevel Modeling Using R
Language: English
Published by Sage Publications, SAGE Publications, Inc, 2022
ISBN 10: 1544324901 ISBN 13: 9781544324906
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal,and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.
