am Dienstag, 29. Oktober 2013
15:30 Uhr
Institut für Medizinische Informatik, Statistik und Dokumentation, Raum S-05-170
LKH-Eingangszentrum, Auenbruggerplatz 2 /5.OG, 8036 Graz

Multiple comparisons for non-Gaussian distributed endpoints - using R

von Prof. Dr. Ludwig A. Hothorn
Institute of Biostatistics, Leibniz University Hannover, Germany


A discrepancy between the MCP-methods assuming Gaussian distribution and homogeneous variances in the literature (& common software), and the practically occurring different types of endpoints in RCT and toxicology exists, namely: i) proportions (e.g. tumor rates), ii) skewed distributed endpoints (e.g. the ASAT enzyme),iii) survival functions, iv) mortality-adjusted tumor rates (poly-3 estimates without cause-of-death information), v) counts with between-subject-variability (overdispersion) (e.g. number of micronuclei), vi) ordered categorical data (e.g. graded histopathological findings). Based on the asymptotic approach in general parametric models (Hothorn et al. 2008) and the R packages multcomp, mratios, MCPAN and SimpComp, by means of case studies the estimation of related simultaneous endpoints for different contrast matrices are demonstrated, such as Dunnett-type, Williams-type and Grand-Mean-type. Moreover, the usefulness of a non-parametric version for relative effects (Konietschke et al. 2012 ) is demonstrated using the R package nparcomp and ratio-to-control tests are explained using the R package, particularly in the case of variance heterogeneity. Finally, user-defined contrast tests, controlling a claim-wise error rate (instead of a family-wise), will be discussed.


Hothorn,T; Bretz,F.and Peter Westfall. Simultaneous inference in general parametric models. Biometrical Journal, 50(3):346-63, (2008).
Konietschke, F;L.A. Hothorn, Brunner, E. Rank-based multiple test procedures and simultaneous confidence intervals. Electronic Journal of Statistics Vol. 6 (2012) 737–758

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