Bayesian Nonparametrics for Causal Inference and Missing Data

• Thorough discussion of both BNP and its interplay with causal inference and missing data • How to use BNP and g-computation for causal inference and nonignorable missingness • How to derive and calibrate sensitivity parameters to assess sensitivity to deviations from uncheckable causal and/or missingness assumptions • Detailed case studies illustrating the application of BNP methods to causal inference and missing data • R-code and/or packages to implement BNP in causal inference and missing data problems

General

Imprint:	Crc Press
Country of origin:	United Kingdom
Series:	Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Release date:	August 2023
First published:	2024
Authors:	Michael J. Daniels • Antonio Linero • Jason Roy
Dimensions:	234 x 156mm (L x W)
Pages:	248
ISBN-13:	978-0-367-34100-8
Categories:	Books
LSN:	0-367-34100-X
Barcode:	9780367341008

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