The jackknife, multicrossvalidation, and analytical formulae methods are discussed and compared with respect to the estimation of shrinkage of the multiple coefficient of correlation. The validation and comparison of the techniques are based on estimates generated from a random data set and a prestructured data set. Multicrossvalidation is demonstrated to be a preferable technique to the jackknife and analytical formulae methods.
Get full access to this article
View all access options for this article.
References
1.
KrusD. J.FullerE. A. (1982). Computer assisted multicrossvalidation in regression analysis. Educational and Psychological Measurement, 42, 187–193.
2.
LordF. M.NovickM. R. (1968). Statistical theories of mental test scores. Reading: Addison-Wesley.
3.
MillerR. G. (1974). The jackknife—A review. Biometrika, 61, 1–15.
4.
OlkinJ.PrattJ. W. (1958). Unbiased estimation of certain correlation coefficients. Annals of Mathematical Statistics, 29, 201–211.
5.
QuenouilleM. H. (1949). Approximate tests of correlation in time-series. Journal of the Royal Statistical Society, 11, 68–84. (Series B.).
6.
ThurstoneL. L. (1947). Multiple factor analysis. Chicago: University of Chicago Press.
7.
TukeyJ. W. (1958). Bias and confidence in not-quite large samples. Annals of Mathematical Statistics, 29, 614.
8.
WherryR. J. (1931). A new formula for predicting the shrinkage of the coefficient of multiple correlation. Annals of Mathematical Statistics, 2, 440–451.