Semiparametric Odds Ratio Model and Its Applications

Author:   Hua Yun Chen
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032159195


Pages:   294
Publication Date:   29 January 2024
Format:   Paperback
Availability:   In Print   Availability explained
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Semiparametric Odds Ratio Model and Its Applications


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Overview

Beginning with familiar models and moving onto advanced semiparametric modelling tools Semiparametric Odds Ratio Model and its Applications introduces readers to a new range of flexible statistical models and provides guidance on their application using real data examples. This books range of real-world examples and exploration of common statistical problems makes it an invaluable reference for research professionals and graduate students of biostatistics, statistics, and other quantitative fields. Key Features: Introduces flexible statistical models that have yet to systematically introduced in course materials. Discusses applications of the proposed modelling framework in several important statistical problems, ranging from biased sampling designs and missing data, graphical models, survival analysis, Gibbs sampler and model compatibility, and density estimation. Includes real data examples to demonstrate the use of the proposed models, and estimation and inference tools.

Full Product Details

Author:   Hua Yun Chen
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.453kg
ISBN:  

9781032159195


ISBN 10:   1032159197
Pages:   294
Publication Date:   29 January 2024
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Dr. Hua Yun Chen received his PhD in Biostatistics from the University of Michigan. He is currently a Professor of Biostatistics at the University of Illinois at Chicago. His research focuses on statistical methods for incompletely observed data, biased sampling, and epidemiological applications.

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