Reference curves based on non-parametric quantile regression.
Reference curves which take time into account, such as those for age, are often required in medicine, but simple systematic and efficient statistical methods for constructing them are lacking. Classical methods are based on parametric fitting (polynomial curves). Semi-parametric methods are also widely used especially in Europe. Here, we propose a new methodology for the estimation of reference intervals for data sets, based on non-parametric estimation of conditional quantiles. The derived methods should be applicable to all clinical (or more generally biological) variables that are measured on a continuous quantitative scale. As an example, we analyse a data set collected to establish reference curves for biophysical properties of the skin of healthy French women. The results are compared to those obtained with Royston's polynomial parametric method and the semi-parametric LMS approach.
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008875:Middle Aged; D012016:Reference Values; D012044:Regression Analysis; D012879:Skin Physiological Phenomena; D018709:Statistics, Nonparametric