Statistical Methods for Handling Incomplete Data e-bog
948,41 DKK
(inkl. moms 1185,51 DKK)
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.a FeaturesUses the mean score equation as a building block for de...
E-bog
948,41 DKK
Forlag
Chapman and Hall/CRC
Udgivet
18 november 2021
Længde
364 sider
Genrer
Probability and statistics
Sprog
English
Format
epub
Beskyttelse
LCP
ISBN
9781000466348
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.a FeaturesUses 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 IntegrationNow 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.