Affordable Access

deepdyve-link
Publisher Website

Sample size determination for studies designed to estimate covariate-dependent reference quantile curves.

Authors
  • Jennen-Steinmetz, Christine1
  • 1 Department of Biostatistics, Central Institute of Mental Health, Medical Faculty Mannheim / Heidelberg University, Mannheim, Germany. , (Germany)
Type
Published Article
Journal
Statistics in Medicine
Publisher
Wiley (John Wiley & Sons)
Publication Date
Apr 15, 2014
Volume
33
Issue
8
Pages
1336–1348
Identifiers
DOI: 10.1002/sim.6024
PMID: 24307204
Source
Medline
Keywords
License
Unknown

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.

Report this publication

Statistics

Seen <100 times