IN some linear regression problems samples may be unwittingly drawn from a heterogeneous population. The exploratory procedure described in this paper can be used to detect heterogeneity in a regression problem associated with the intercept.
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References
1.
Aggarwal, L. K. (1981). An exploratory method for the classification of social-political-economic entities for use in regression. Proceedings of the 13th Annual Meeting, American Institute for Decision Sciences, Boston, p. 413.
2.
Aversen, J. N. and McCabe, G. P., Jr. (1975). Subset selection problems for variances with applications to regression analysis. Journal of the American Statistical Association, 70, 166-170.
3.
Cleary, T. A. (1966). An individual differences model for multiple regression. Psychometrika, 31, 215-224.
4.
Crutcher, H. L. and Joiner, R. L. (1977). Separation of mixed data sets into homogeneous sets. NOAA Technical Report EDS 19, National Oceanic and Atmospheric Administration, U.S. Department of Commerce.
5.
Diggle, P. J. (1977). The detection of random heterogeneity in plant populations. Biometrics, 33, 390-394. -
6.
Gupta, S. S. and Sobel, M. (1962). On selecting a subset containing the population with the smallest variance. Biometrika, 49, 495-507.
7.
Hamilton, B. L. (1977). An empirical investigation of the effects of heterogeneous regression slopes in analysis of covariance. Educational And Psychological Measurement, 37, 701-712.
8.
Landwehr, J. M. , Pregibon, D., and Shoemaker, A. (1984). Graphical methods for assessing logistic regression models. Journal of the American Statistical Association, 79(385), 701-712.
9.
Rao, C. R. (1970). Advanced statistical methods in biometric research. Darien: Hafner Publishing Co.
10.
Rulon, P. J. , Tiedeman, D. V., Tatsuoka, M. M., and Langmuir, C. R. (1967). Multivariate statistics for personnel classification. New York: Wiley.
11.
Saxena, K. P. (1971). On power of sometimes pool tests and the Bayes rule for intercepts in linear regression models assuming heterogeneity of variances. Estadistica, pp. 158-166.
12.
Schnute, J. (1984). Linear mixtures: A new approach to bivariate trend lines. Journal of the American Statistical Association, 79(385), 1-8.
13.
Tukey, J. W. (1977). Exploratory data analysis. New York: Addison-Wesley.
