Two-sample tests and one-way MANOVA for multivariate biomarker data with nondetects
2016 (English)In: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 35, no 20, 3623-3644 p.Article in journal (Refereed) Published
Testing whether the mean vector of a multivariate set of biomarkers differs between several populations is an increasingly common problem in medical research. Biomarker data is often left censored because some measurements fall below the laboratory's detection limit. We investigate how such censoring affects multivariate two-sample and one-way multivariate analysis of variance tests. Type I error rates, power and robustness to increasing censoring are studied, under both normality and non-normality. Parametric tests are found to perform better than non-parametric alternatives, indicating that the current recommendations for analysis of censored multivariate data may have to be revised.
Place, publisher, year, edition, pages
2016. Vol. 35, no 20, 3623-3644 p.
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:uu:diva-283203DOI: 10.1002/sim.6945ISI: 000380728800013PubMedID: 26999657OAI: oai:DiVA.org:uu-283203DiVA: diva2:918773
FunderSwedish National Infrastructure for Computing (SNIC), SNIC 2014-1-340