The publications on dose-response analysis in the recent years is fairly clear divided into modelling (ie assuming dose as a quantitative covariate) and trend tests (ie assuming dose as a qualitative factor). Both approaches show advantages and disadvantages. What is missing is a joint approach. Three components are required: i) a quasilinear regression approach, namely the maximum of arithmetic, ordinal and logarithmic dose metameter models according to Tukey et al. (1985) ii) a contrast test for a maximum of Williams-type contrasts according to Bretz and Hothorn (2003) iii) the multiple marginal models approach according to Pipper et al. (2011) allowing the distribution of the maximum of multiple glmm’s.
This new versatile trend test provides three advantages: 1) almost powerful for any shape of the dose-.response (including sublinear and supralinear) 2) problem-related interpretability based on confidence limits of slopes and/or contrasts 3) widespread use in the glmm.
By means of the R library(tukeytrend) (Schaarschmidt et al., 2017) case studies for multinomial vector comparisons, multiple binary endpoints, bivariate different scaled endpoints and ANCOVA-adjusted dose-response data will be explained.
