library(ez)
lok = read.table(file.path(pfad, "lok.txt"))
ezANOVA(lok, .(slopes), .(Spr), .(Kons, P), .(G))
source(file.path(pfad, "phoc.txt"))
lok.ph1 = phoc(lok, .(slopes), .(Spr), .(Kons, P))
phsel(lok.ph1[[1]])
phsel(lok.ph1[[1]], 2)

library(lme4)
o = lmer(slopes ~ Kons * G * P + (1 | Spr), data = lok)
o2 = lmer(slopes ~ Kons + G + P + (1 | Spr),  data = lok)
# any interactions significant? Yes
anova(o, o2)
# test on G:Kons. NS
o3 = update(o2, ~ . +G:Kons)
anova(o2, o3)

# test on G:P. NS
o4 = update(o2, ~ . +G:P)
anova(o2, o4)

# test on Kons:P. Sig.
o5 = update(o2, ~ . +Kons:P)
# also works
o5b = update(o2, ~ . +P:Kons)
anova(o2, o5)

# test on G:Kons:P
#  Need to compare model with interaction terms minus this one. Sig.
o6 = update(o, ~ . -Kons:P:G)
anova(o, o6)

# post-hoc, Kons * P
lab = factor(paste(lok$Kons, lok$P))
o8 = lmer(slopes ~ lab + (1 | Spr), data = lok)
library(multcomp)
summary(glht(o8, linfct=mcp(lab="Tukey")))