Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with income surveys. Many traditional applications are known but information about these procedures is often difficult to achieve. The author proposes the use of multiple imputation (MI) techniques using informative prior distributions to overcome the conditional independence assumption. By means of MI sensitivity of the unconditional association of the variables not jointy observed can be displayed. An application of the alternative approaches with real world data concludes the book.
| ISBN: | 9780387955162 |
| Publication date: | 4th September 2002 |
| Author: | Susanne Rässler |
| Publisher: | Springer an imprint of Springer New York |
| Format: | Paperback |
| Pagination: | 238 pages |
| Series: | Lecture Notes in Statistics |
| Genres: |
Probability and statistics |
Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with income surveys. Many traditional applications are known but information about these procedures is often difficult to achieve. The author proposes the use of multiple imputation (MI) techniques using informative prior distributions to overcome the conditional independence assumption. By means of MI sensitivity of the unconditional association of the variables not jointy observed can be displayed. An application of the alternative approaches with real world data concludes the book.
Statistical Matching features in the following genres: Probability and statistics
Statistical Matching is available in Paperback
Statistical Matching was written by Susanne Rässler and published by Springer an imprint of Springer New York
Statistical Matching has 238 pages
Yes it is part of Lecture Notes in Statistics series