Some Aspects of Nonorthogonal Data Analysis
- 1 April 1973
- journal article
- research article
- Published by Taylor & Francis in Journal of Quality Technology
- Vol. 5 (2) , 67-79
- https://doi.org/10.1080/00224065.1973.11980577
Abstract
It is known that regression results can be misleading when the predictor variables (x's) are highly correlated (nonorthogonal). The objective of this paper is to present some guidelines for deciding when the correlations among the x's are so large that the numerical accuracy and/or physical interpretation of regression results should be questioned. A measure of nonorthogonality is presented and the effects of correlated x's and poor model formulation on tho estimated coefficients are discussed. Emphasis is placed on the practical interpretation of regression results. Two illustrative examples are presented.Keywords
This publication has 10 references indexed in Scilit:
- Design and Analysis of Mixture ExperimentsJournal of Quality Technology, 1971
- A New Method for Examining Rounding Error in Least-Squares Regression Computer ProgramsJournal of the American Statistical Association, 1971
- Fitting Equations to Mixture Data with Restraints on CompositionsJournal of Quality Technology, 1970
- Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear EstimationTechnometrics, 1970
- Ridge Regression: Applications to Nonorthogonal ProblemsTechnometrics, 1970
- Ridge Regression: Biased Estimation for Nonorthogonal ProblemsTechnometrics, 1970
- Uniform Shell DesignsJournal of the Royal Statistical Society Series C: Applied Statistics, 1970
- Extreme Vertices Design of Mixture ExperimentsTechnometrics, 1966
- Experiments with MixturesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1958
- Part II. The value and the limitations of highspeed turbo‐exhausters for the removal of tar‐fog from carburetted water‐gasJournal of the Society of Chemical Industry, 1946