Polynomial regression models are usually fit using the method of least squares.
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Alternatives to difference scores : Polynomial regression analysis and response surface methodology.
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A pioneering optimal design for polynomial regression was suggested by Gergonne in 1815.
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Some of these methods make use of a localized form of classical polynomial regression.
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The polynomial regression equation commonly used in person-environment fit research is as follows:
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On the use of polynomial regression equations as an alternative to difference scores in organizational research.
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Therefore, non-parametric regression approaches such as smoothing can be useful alternatives to polynomial regression.
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*Microsoft Excel makes use of polynomial regression when fitting a trendline to data points on an X Y scatter plot.
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It is often difficult to interpret the individual coefficients in a polynomial regression fit, since the underlying monomials can be highly correlated.
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Although polynomial regression is technically a special case of multiple linear regression, the interpretation of a fitted polynomial regression model requires a somewhat different perspective.
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