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Statistical Methods for Handling Incomplete Data

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SKU 9780367280543 Categories ,
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Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. This book covers the most up-to-date statistical theories and computational methods for analyzing i...

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Description

Product ID:9780367280543
Product Form:Hardback
Country of Manufacture:US
Title:Statistical Methods for Handling Incomplete Data
Authors:Author: Jae Kwang Kim, Jun Shao
Page Count:380
Subjects:Probability and statistics, Probability & statistics, Biology, life sciences, Biology, life sciences
Description:Select Guide Rating
Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. This book covers the most up-to-date statistical theories and computational methods for analyzing incomplete data.

Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and computational methods for analyzing incomplete data.

 

Features

  • Uses the mean score equation as a building block for developing the theory for missing data analysis
  • Provides comprehensive coverage of computational techniques for missing data analysis
  • Presents a rigorous treatment of imputation techniques, including multiple imputation fractional imputation
  • Explores the most recent advances of the propensity score method and estimation techniques for nonignorable missing data
  • Describes a survey sampling application
  • Updated with a new chapter on Data Integration
  • Now includes a chapter on Advanced Topics, including kernel ridge regression imputation and neural network model imputation

The book is primarily aimed at researchers and graduate students from statistics, and could be used as a reference by applied researchers with a good quantitative background. It includes many real data examples and simulated examples to help readers understand the methodologies.


Imprint Name:Chapman & Hall/CRC
Publisher Name:Taylor & Francis Ltd
Country of Publication:GB
Publishing Date:2021-11-19