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Linear Transformations of Polynomial Regression Models
Gary L. Griepentrog, J. Michael Ryan and L. Douglas Smith
The American Statistician
Vol. 36, No. 3, Part 1 (Aug., 1982), pp. 171-174
Stable URL: http://www.jstor.org/stable/2683171
Page Count: 4
You can always find the topics here!Topics: Polynomials, Statistical models, Linear transformations, Regression analysis, Temperature, Parametric models, Statistical significance, Matrices, Statistics, Linear regression
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Statistical texts differ in the ways they test the significance of coefficients of lower-order terms in polynomial regression models. One reason for this difference is probably the concern of some authors that t ratios for the regression coefficients of lower-order terms may change as a result of linear scale transformations of the independent variables. Empiricists generally report tests of these terms and attempt to interpret their meanings. This paper succinctly demonstrates how linear transformations of polynomial regression models affect tests of statistical significance for individual parameters.
The American Statistician © 1982 American Statistical Association