Nonlinear Quantile Regression for Longitudinal Data
2005 (English)Licentiate thesis, monograph (Other scientific)
The overall objective of the two papers in this thesis is to examine the properties of the weighted nonlinear quantile regression estimator for the analysis of longitudinal data. To this end, the question of which weights to be used, the bias of the estimator and the possibility to calculate confidence intervals has to be examined. The focus is on small samples, since this is the most common case for real world applications in biostatistics.
Place, publisher, year, edition, pages
2005. , 75 p.
bootstrap, dependent errors, median regression, Monte Carlo simulation, panel data, repeated measures
Probability Theory and Statistics Bioinformatics (Computational Biology)
IdentifiersURN: urn:nbn:se:uu:diva-86355OAI: oai:DiVA.org:uu-86355DiVA: diva2:117164