It seems that statistical matching splits the field of statistics in two. Statistical matching is blamed and repudiated by sceptical theoretical and practical statisticians about the power of matching techniques. This is reported, e.g., by Moriarity and Scheuren (2001), Judkins (1998), Gabler (1997), Bennike (1987), Rodgers (1984), Woodbury (1983), and Sims (1972a and b). On the other hand, famous statistical offices such as Statistics Canada as well as market research companies especially in Europe have done or are still doing statistical matching which in Europe is typically called data fusion. However, from time to time there are reports published stating that data from different sources have been matched successfully. Positive experiences with statistical matching have been published in a wide variety of journals or as internal reports or working papers, e.g., by Aluja-Banet and Thio (2001), Wendt (1976, 1986, 2000), Kovacevic and Liu (1994), Liu and Kovacevic (1996, 1997, 1998), Roberts (1994), Baker (1990), Baker et al. (1989), Antoine (1987), Antoine and Santini (1987), Scheler and Wiegand (1987), Wiegand (1986), Okner (1974), Ruggles and Ruggles (1974), Ruggles et al. (1977), and Okner (1972a and b).
KeywordsMultiple Imputation Statistical Match Conditional Independence Record Linkage Markov Chain Monte Carlo Method
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