Statistical Modelling 7 (2007), 363376
Worm plot to diagnose fit in quantile regression
Stef van Buuren
Department of Statistics,
TNO Quality of Life,
P.O. Box 2215,
NL2301 NE Leiden
The Netherlands
and
Department of Methodology and Statistics,
Faculty of Social Sciences,
University of Utrecht,
The Netherlands
eMail:
Stef.vanBuuren@tno.nl
Abstract:
The worm plot is a series of detrended Q-Q plots, split by covariate
levels. The worm plot is a diagnostic tool for visualizing how well a
statistical model fits the data, for finding locations at which the
fit can be improved, and for comparing the fit of different models. This
paper shows how the worm plot can be used in conjunction with quantile
regression. No parametric distributional assumptions are needed to create
the worm plot. We fitted both an LMS and a quantile regression model
on Dutch height data. The worm plot shows that the quantile regression
model is superior to the LMS model in terms of fit. At the same time,
it also contains a warning that the particular quantile model used may
actually overfit the data. The resulting quantile curves are wiggly at
the extremes, and appear less well suited for drawing growth diagrams.
The paper concludes that the worm plot is a natural diagnostic tool
for quantile regression.
Keywords:
centiles; growth diagrams; LMS model; P-P plot; Q-Q plot; smoothing
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