Statistical Matching

1. Front Matter

   Pages N2-xviii

   PDF

2. Introduction

   • Susanne Rässler

   Pages 1-14

3. Frequentist Theory of Statistical Matching

   • Susanne Rässler

   Pages 15-43

4. Practical Applications of Statistical Matching

   • Susanne Rässler

   Pages 44-70

5. Alternative Approaches to Statistical Matching

   • Susanne Rässler

   Pages 71-127

6. Empirical Evaluation of Alternative Approaches

   • Susanne Rässler

   Pages 128-199

7. Synopsis and Outlook

   • Susanne Rässler

   Pages 200-207

8. Back Matter

   Pages 208-241

   PDF

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.

• Area
• Erlang
• Fusion
• Outlook
• Simula
• data analysis
• database
• distribution
• evaluation
• history of mathematics
• information
• production
• set
• statistics
• story

"Statistical matching is one of the methods for the imputation of missing results from survey sampling…This book is totally focused on methods, applications, and results. It devotes little space to the presentation and derivation of various theorems." Technometrics, May 2004

• Institute of Statistic and Econometrics, University of Erlangen-Nürnberg, Nürnberg, Germany

  Susanne Rässler

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