Statistical Matching / Wiley Series in Survey Methodology (PDF)

There is more statistical data produced in today's modern
society than ever before. This data is analysed and
cross-referenced for innumerable reasons. However, many data sets
have no shared element and are harder to combine and therefore
obtain any meaningful inference from. Statistical matching allows
just that; it is the art of combining information from different
sources (particularly sample surveys) that contain no common unit.
In response to modern influxes of data, it is an area of rapidly
growing interest and complexity. Statistical Matching: Theory
and Practice introduces the basics of statistical matching,
before going on to offer a detailed, up-to-date overview of the
methods used and an examination of their practical applications.

* Presents a unified framework for both theoretical and practical
aspects of statistical matching.

* Provides a detailed description covering all the steps needed
to perform statistical matching.

* Contains a critical overview of the available statistical
matching methods.

* Discusses all the major issues in detail, such as the
Conditional Independence Assumption and the assessment of
uncertainty.

* Includes numerous examples and applications, enabling the
reader to apply the methods in their own work.

* Features an appendix detailing algorithms written in the R
language.

Statistical Matching: Theory and Practice presents a
comprehensive exploration of an increasingly important area. Ideal
for researchers in national statistics institutes and applied
statisticians, it will also prove to be an invaluable text for
scientists and researchers from all disciplines engaged in the
multivariate analysis of data collected from different sources.