Published by Chapman and Hall/CRC, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
Language: English
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Published by Taylor & Francis Ltd, 2023
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Published by Chapman and Hall/CRC, 2023
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
Language: English
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
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Published by Taylor & Francis Ltd, London, 2023
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Add to basketHardcover. Condition: new. Hardcover. Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies. Unlike parametric methods, the BNP approach can account for...
Published by Taylor & Francis Ltd, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
Language: English
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
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Add to basketCondition: New. Dr. Daniels received his undergraduate degree from Brown University in Applied Mathematics and doctoral degree from Harvard University in Biostatistics. He has been on the faculty at Iowa State and University of Texas at Austin. C.
Published by Taylor & Francis Ltd, 2023
ISBN 10: 036734100X ISBN 13: 9780367341008
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Add to basketHardcover. Condition: Brand New. 252 pages. 9.19x6.13x0.87 inches. In Stock.
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Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal...
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Add to basketHardcover. Condition: Brand New. 252 pages. 9.19x6.13x0.87 inches. In Stock. This item is printed on demand.
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies....