Förlagets beskrivning
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data.
Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area
Fler böcker av författarna
Liknande böcker
Recensioner
Den här boken har tyvärr inte några recensioner ännu. Om du redan läst boken, skriv en recension!
Recensera boken
Skriv en recension och dela dina åsikter med andra. Försök att fokusera på bokens innehåll. Läs våra instruktioner för mer information.
Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives
Bokrecensioner » Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives (Wiley Series in Probability and Statistics)
|
|
 |
|
|
|
|
