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CIcomp(mixProp, modelList, EDvec)
CIcompX(mixProp, modelList, EDvec, EDonly = FALSE)
plotFACI(effList, indAxis = c("ED", "EF"), caRef = TRUE,
showPoints = FALSE, add = FALSE, ylim, ...)drm with the model fit
for single mixture ratio being the first element, followed by the 2 model fits of the pure
substances.CIcompX.CIcomp returns a matrix which one row per ED value. Columns contain
estimated combination indices, their standard errors and 95% confidence intervals,
p-value for testing CI=1, estimated ED values for the mixture data and assuming
concentration addition (CA) with corresponding standard errors.CIcompX returns similar output both for effective doses and effects (as a
list of matrices).
CIcomp calculates the classical combination index for effective doses whereas CIcompX calculates the combination index also for effects as proposed by
Martin-Betancor et al. (2015); for details and examples using "drc" see the supplementary material of this paper. The function plotFACI may be used to visualize the
calculated combination index as a function of the fraction affected.
mixture for simultaneous modelling of several mixture ratios, but only at the ED50 level.See also the help page for metals.
## Fitting marginal models for the 2 pure substances
acidiq.0 <- drm(rgr ~ dose, data = subset(acidiq, pct == 999 | pct == 0), fct = LL.4())
acidiq.100 <- drm(rgr ~ dose, data = subset(acidiq, pct == 999 | pct == 100), fct = LL.4())
## Fitting model for single mixture with ratio 17:83
acidiq.17 <- drm(rgr ~ dose, data = subset(acidiq, pct == 17 | pct == 0), fct = LL.4())
## Calculation of combination indices based on ED10, ED20, ED50
CIcomp(0.17, list(acidiq.17, acidiq.0, acidiq.100), c(10, 20, 50))
## CI>1 significantly for ED10 and ED20, but not so for ED50
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