title: Sample size determination for studies designed to estimate covariate-dependent reference quantile curves.
abstract: Accuracy and sample size issues concerning the estimation of covariate-dependent quantile curves are considered. It is proposed to measure the precision of an estimate of the pth quantile at a given covariate value by the probability with which this estimate lies between the p1 th and p2 th quantile, where p1  < p < p2 . Requiring that this probability exceeds a given confidence bound for all covariate values in a specified range leads to a sample size criterion. Approximate formulae for the precision and sample size are derived for the normal parametric regression approach and for the semiparametric quantile regression method. A simulation study is performed to evaluate the accuracy of the approximations. Numerical evaluations show that rather large numbers of subjects are needed to construct quantile curves with a reasonable amount of accuracy, especially if the quantile regression method is applied.
authors.affiliation: Department of Biostatistics, Central Institute of Mental Health, Medical Faculty Mannheim / Heidelberg University, Mannheim, Germany.
authors.forename: Christine
authors.initials: C
authors.lastname: Jennen-Steinmetz
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D003198:Computer Simulation; D006801:Humans; D008297:Male; D008875:Middle Aged; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000175:diagnosis; D012044:Regression Analysis; D015203:Reproducibility of Results; D012107:Research Design; D018401:Sample Size
chemical_list: D017430:Prostate-Specific Antigen
keywords: percentiles; precision; quantile curve; quantile regression; reference limits; sample size