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It is both a privilege and a challenge to summarize Ray Carroll’s contributions in measurement error. Ray literally wrote the book on the topic with coauthors David Ruppert, Len Stefanski, and Ciprian Crainiceanu (Carroll et al., 2006), and his fingerprints are present in a huge amount of published research on measurement error over the past 30 years. In addition to the book, Ray has authored or coauthored close to 100 papers involving measurement error alone, addressing a vast array of problems. His work covers models from the fairly simple to the very complex with an emphasis ranging from the relatively applied to the highly theoretical. Our detailed discussion of Ray’s work concentrates heavily on the twelve papers appearing in this volume, although this only scratches the surface of his contributions. We first discuss parametric models ([MEM-1]-[MEM-4] and [MEM-7]-[MEM-9]), then turn to non-parametric and semi-parametric models including deconvolution problems ([MEM-5],[MEM-6],[MEM-10]-[MEM-11]).
KeywordsMeasurement Error Statistical Theory Huge Amount Vast Array Deconvolution Problem
Other publications by Ray Carroll cited in this chapter.
- Carroll, R. J. and Ruppert, D. (1996). The use and misuse of orthogonal regression in linear errors-in-variables models. American Statistician, 50, 1–6.Google Scholar
Publications by other authors cited in this chapter.
- Brown, P. J. and Fuller, W. A. (1990). Statistical Analysis of Measurement Error Models and Applications: Proceedings of the AMS-IMS-SIAM Joint Summer Research Conference, June 10–16, 1989. Providence: American Mathematical Society.Google Scholar
- Byar, D. P. and Gail, M. (1989). Introduction. Errors-in-variables workshop. Statistics in Medicine, 8, 1027–1029.Google Scholar