param = read.table(file.path(pfad, "param.txt"))
ezANOVA(param, .(slopes), .(Vpn), .(Cont), .(Group))
##################################################
noise = read.table(file.path(pfad, "noise.txt"))
ezANOVA(noise, .(rt), .(Subj), .(Type, Noise))
boxplot(rt ~ Type * Noise, data = noise)
noise.ph = phoc(noise, .(rt), .(Subj), .(Type, Noise))
phsel(noise.ph[[1]])
phsel(noise.ph[[1]], 2)
##################################################
auf = read.table(file.path(pfad, "auf.txt"))
ezANOVA(auf, .(RT), .(Vpn), .(Monat), .(Lang))
ph = phoc(auf, .(RT), .(Vpn), .(Monat, Lang))
phsel(ph[[1]])
phsel(ph[[1]], 2)
##################################################
lok = read.table(file.path(pfad, "lok.txt"))
ezANOVA(lok, .(slopes), .(Spr), .(Kons, P), .(G))
lok.ph1 = phoc(lok, .(slopes), .(Spr), .(Kons, P))
phsel(lok.ph1[[1]])
phsel(lok.ph1[[1]], 2)
lok.ph2 = phoc(lok, .(slopes), .(Spr), .(Kons, P, G))
phsel(lok.ph2[[1]], 1)
phsel(lok.ph2[[1]], 2)
phsel(lok.ph2[[1]], 3)
##################################################

ezANOVA(rating, .(Rating), .(Vpn), .(Gram, Type, Fam), .(Lang))
#####################################################

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


rtdaten = read.table(file.path(pfad, "rtdaten.txt"))
boxplot(RT ~ Group * Cons, data = rtdaten)
boxplot(RT ~ Pair * Cons, data = rtdaten)
ezANOVA(rtdaten, .(RT), .(Listener), .(Cons, Pair), .(Group))
# wird nicht gehen
phoc(rtdaten, .(RT), .(Listener), .(Group, Cons))
# aggregate
rtdaten2 = with(rtdaten, aggregate(RT, list(Group, Cons, Listener), mean))
names(rtdaten2) = c("Group", "Cons", "Listener", "RT")
r.ph = phoc(rtdaten2, .(RT), .(Listener), .(Cons, Group))
phsel(r.ph[[1]])
phsel(r.ph[[1]], 2)

r2.ph = phoc(rtdaten, .(RT), .(Listener), .(Pair, Cons))
phsel(r2.ph[[1]])
phsel(r2.ph[[1]], 2)

# look at d:same - r:same
temp = rtdaten$Cons == "d" & rtdaten$Pair == "same"
a = rtdaten[temp,]
temp = rtdaten$Cons == "r" & rtdaten$Pair == "same"
b = rtdaten[temp,]
m = match(a$Listener, b$Listener)
# hugely different from zero
boxplot(a$RT - b$RT)

# compare with d.diff and r.diff
temp = rtdaten$Cons == "d" & rtdaten$Pair == "diff"
a = rtdaten[temp,]
temp = rtdaten$Cons == "r" & rtdaten$Pair == "diff"
b = rtdaten[temp,]
m = match(a$Listener, b$Listener)
# Almost at zero
boxplot(a$RT - b$RT)

###############################################
ice.ag = with(ice, aggregate(Dauer, list(Sprecher, Type, Vokal, Stop), mean))
names(ice.ag) = c("Sprecher", "Type", "Vokal", "Stop", "Dauer")
ezANOVA(ice.ag, .(Dauer), .(Sprecher), .(Type, Vokal, Stop))

# aggregate over Type and Vokal
ice.ag2 = with(ice.ag, aggregate(Dauer, list(Sprecher, Type, Vokal), mean))
names(ice.ag2) = c("Sprecher", "Type", "Vokal", "Dauer")
ph = phoc(ice.ag2, .(Dauer), .(Sprecher), .(Type, Vokal))
phsel(ph[[1]])
phsel(ph[[1]], 2)

ph = phoc(ice.ag, .(Dauer), .(Sprecher), .(Type, Vokal, Stop))
phsel(ph[[1]])

###############################################
vcv = read.table(file.path(pfad, "vcv.txt"))
vcv.ag = with(vcv, aggregate(RT, list(Subject, Vowel, Lang, Left, Right), mean))
names(vcv.ag) = c("Subj", "Vowel", "Lang", "Left", "Right", "RT")
vcv.ez = ezANOVA(vcv.ag, .(RT), .(Subj), .(Vowel, Left, Right), .(Lang))
vcv.ez

vcv.ag2 = with(vcv, aggregate(RT, list(Subject, Vowel, Right), mean))

names(vcv.ag2) = c("Vpn", "Vok", "Right", "RT")
ph = phoc(vcv.ag2, .(RT), .(Vpn), .(Vok, Right))