compareGrowthCurves(group, y, levels=NULL, nsim=100, fun=meanT, times=NULL, verbose=TRUE, adjust="holm")
compareTwoGrowthCurves(group, y, nsim=100, fun=meanT)
plotGrowthCurves(group, y, levels=sort(unique(group)), times=NULL, col=NULL,...)compareGrowthCurves but not in compareTwoGrowthCurves.group. Missing values are allowed.meanT.p.adjust.plot()compareTwoGrowthCurves returns a list with two components, stat and p.value, containing the observed statistics and the estimated p-value. compareGrowthCurves returns a data frame with components
returns a data frame with componentscompareTwoGrowthCurves performs a permutation test of the difference between two groups of growth curves.
compareGrowthCurves does all pairwise comparisons between two or more groups of growth curves.
Accurate p-values can be obtained by setting nsim to some large value, nsim=10000 say.
Baldwin, T., Sakthianandeswaren, A., Curtis, J., Kumar, B., Smyth, G. K., Foote, S., and Handman, E. (2007). Wound healing response is a major contributor to the severity of cutaneous leishmaniasis in the ear model of infection. Parasite Immunology 29, 501-513. http://www.blackwell-synergy.com/doi/abs/10.1111/j.1365-3024.2007.00969.x
meanT, compareGrowthCurves, compareTwoGrowthCurves
# A example with only one time
data(PlantGrowth)
compareGrowthCurves(PlantGrowth$group,as.matrix(PlantGrowth$weight))
# Can make p-values more accurate by nsim=10000
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