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Confidence regions for INDSCAL using the jackknife and bootstrap techniques
Authors:Sharon L Weinberg  J Douglas Carroll  Harvey S Cohen
Institution:(1) AT&T Bell Laboratories, USA;(2) AT&T Information Systems, USA;(3) Program of Educational Statistics, New York University, 933 Shimkin Hall, 10003 New York, N.Y.
Abstract:Bootstrap and jackknife techniques are used to estimate ellipsoidal confidence regions of group stimulus points derived from INDSCAL. The validity of these estimates is assessed through Monte Carlo analysis. Asymptotic estimates of confidence regions based on a MULTISCALE solution are also evaluated. Our findings suggest that the bootstrap and jackknife techniques may be used to provide statements regarding the accuracy of the relative locations of points in space. Our findings also suggest that MULTISCALE asymptotic estimates of confidence regions based on small samples provide an optimistic view of the actual statistical reliability of the solution. The authors wish to thank Geert DeSoete, Richard A. Harshman, William Heiser, Jon Kettenring, Joseph B. Kruskal, Jacqueline Meulman, James O. Ramsay, John W. Tukey, Paul A. Tukey, and Mike Wish. Sharon L. Weinberg is a consultant at AT&T Bell Laboratories, Murray Hill, New Jersey 07974.
Keywords:Individual differences  multidimensional scaling  stability  standard errors  pseudovalues  maximum likelihood  resampling schemes
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