Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
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Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
Language: English
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Published by Sage Publications Ltd, 2013
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Language: English
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Add to basketHardcover. Condition: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 3.04.
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Published by SAGE Publications Ltd, 2013
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Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
Language: English
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Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
Language: English
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Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
Language: English
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Published by SAGE Publications Ltd, 2013
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Language: English
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Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
Language: English
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Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
Language: English
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Leading contributors combine practical pieces with overviews of the state of the art in the field, making this handbook essential reading for any student or researcher looking to apply multilevel techniques in their own researchIn this important new.
Published by SAGE Publications Ltd, 2013
ISBN 10: 0857025643 ISBN 13: 9780857025647
Language: English
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this important new Handbook, the editors have gathered together a range of leading contributorsto introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field.Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines.Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.