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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.
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.
"Those interested in statistical matching will find this book very useful." ( Technometrics, August 2007)
"My compliments to the authors for making these (seemingly) arcane ideas available to a whole new generation of statisticians and economists." (Journal of the American Statistical Association, September 2007)
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