title: QQ-plots for assessing distributions of biomarker measurements and generating defensible summary statistics.
abstract: One of the main uses of biomarker measurements is to compare different populations to each other and to assess risk in comparison to established parameters. This is most often done using summary statistics such as central tendency, variance components, confidence intervals, exceedance levels and percentiles. Such comparisons are only valid if the underlying assumptions of distribution are correct. This article discusses methodology for interpreting and evaluating data distributions using quartile-quartile plots (QQ-plots) and making decisions as to how to treat outliers, interpreting effects of mixed distributions, and identifying left-censored data. The QQ-plot graph is shown to be a simple and elegant tool for visual inspection of complex data and deciding if summary statistics should be performed after log-transformation.
authors.affiliation: National Exposure Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
authors.forename: Joachim D
authors.initials: JD
authors.lastname: Pleil
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D001944:Breath Tests / Q000379:methods*; D005260:Female; D006801:Humans; D057230:Limit of Detection; D008297:Male; D015233:Models, Statistical; D014050:Toluene / Q000032:analysis
chemical_list: D015415:Biomarkers; D014050:Toluene