This analysis explores regression techniques utilizing quadratic fits, suggesting improvements through coefficient estimates and generalized linear models.
Quadratic fits are often used in regression and other modeling projects as either the whole of a model or part of a larger model. In this column, I discuss various small Stata devices that may help, including the twoway qfit command, calculation of the turning point position from coefficient estimates, and plotting the fitted curve over a wider range. The main principles carry over from regression to various more complicated models such as generalized linear models. A specific example is the model known in statistical ecology as Gaussian logit, which is just a logit regression fitting a unimodal bell-like curve to a proportion as a quadratic function of some controlling variable. The column includes commentary on wider historical, scientific, and statistical aspects of quadratic fits, with some remarks on their limitations and alternatives.
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Nicholas J Cox (2025) studied this question.
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