Abstract
Orthogonal designs for factors with two levels can be fit using least squares. The orthogonality of the contrasts allows each coefficient to be estimated independently of the other variables in the model.
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References
Box, G. E. P, Hunter, J. S., & Hunter, W. G. (2005). Statistics for experimenters (2nd ed.). New York, NY: Wiley.
Kuehl, R. O. (1994). Statistical principles of research design and analysis. Belmont, CA: Duxbury.
Ledolter, J., & Swersey, A. J. (2007). Testing 1-2-3 experimental design with applications in marketing and service operations. Stanford, CA: Stanford University Press.
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Olive, D.J. (2017). Orthogonal Designs. In: Linear Regression. Springer, Cham. https://doi.org/10.1007/978-3-319-55252-1_8
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DOI: https://doi.org/10.1007/978-3-319-55252-1_8
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