#############################################
#### ANOVA for conditions EXP, USP, ANOM #### 
#############################################

library(ez)
library(reshape2)
library(pastecs)

daten <- read.csv("EEGData_3cond_csv.CSV", sep=";")


##### N400 Analysis
n400 <- subset(daten, daten$time < 500 & daten$time > 300)

n400AOV <- melt(n400, id = (c("subject", "time", "cond")), 
                variable.name = "electrode",
                value.name = "volt")

n400AOV <- aggregate(volt ~ subject + cond + electrode, data = n400AOV, FUN = mean)

n400AOV$subject <- factor(n400AOV$subject)
n400AOV$cond <- factor(n400AOV$cond)

ezANOVA(data = n400AOV,
        dv = volt,
        wid = subject,
        within = cond,
        type = 3)

ezStats(data = n400AOV,
        dv = volt,
        wid = subject,
        within = cond,
        type = 3)


n400AOV <- aggregate(volt ~ subject + cond, data = n400AOV, FUN = mean)

pairwise.t.test(n400AOV$volt, n400AOV$cond, paired = TRUE, p.adjust.method = "bonf")
pairwise.t.test(n400AOV$volt, n400AOV$cond, paired = TRUE, p.adjust.method = "none")

t.test(n400AOV$volt[n400AOV$cond == "EXP "], n400AOV$volt[n400AOV$cond == "USP "], paired = TRUE)
t.test(n400AOV$volt[n400AOV$cond == "EXP "], n400AOV$volt[n400AOV$cond == "ANOM"], paired = TRUE)
t.test(n400AOV$volt[n400AOV$cond == "USP "], n400AOV$volt[n400AOV$cond == "ANOM"], paired = TRUE)

by(n400AOV$volt, list(n400AOV$cond), stat.desc, basic = FALSE)


##### 600 - 1000 ms Analysis posterior
P600 <- subset(daten, daten$time < 1000 & daten$time > 600)

# Electrodes based on DeLong et al.
P600 <- P600[,c("subject", "cond", "time", "Cz", "CP1", "CP2", "P3", "Pz", "P4", "POz")]

P600 <- melt(P600, id = (c("subject", "time", "cond")), 
             variable.name = "electrode",
             value.name = "volt")

P600 <- aggregate(volt ~ subject + cond + electrode, data = P600, FUN = mean)

P600$subject <- factor(P600$subject)
P600$cond <- factor(P600$cond)

ezANOVA(data = P600,
        dv = volt,
        wid = subject,
        within = cond,
        type = 3)

ezStats(data = P600,
        dv = volt,
        wid = subject,
        within = cond,
        type = 3)

P600 <- aggregate(volt ~ subject + cond, data = P600, FUN = mean)

pairwise.t.test(P600$volt, P600$cond, paired = TRUE, p.adjust.method = "bonf")
pairwise.t.test(P600$volt, P600$cond, paired = TRUE, p.adjust.method = "none")

t.test(P600$volt[P600$cond == "EXP "], P600$volt[P600$cond == "USP "], paired = TRUE)
t.test(P600$volt[P600$cond == "EXP "], P600$volt[P600$cond == "ANOM"], paired = TRUE)
t.test(P600$volt[P600$cond == "USP "], P600$volt[P600$cond == "ANOM"], paired = TRUE)

by(P600$volt, list(P600$cond), stat.desc, basic = FALSE)


##### 600 - 1000 ms Analysis anterior
P600 <- subset(daten, daten$time < 1000 & daten$time > 600)

# Elektroden based on DeLong et al.
P600 <- P600[,c("subject", "cond", "time", "Fp1", "Fpz", "F3", "F7", "Fz", "FC5", "T7")]

P600 <- melt(P600, id = (c("subject", "time", "cond")), 
             variable.name = "electrode",
             value.name = "volt")

P600 <- aggregate(volt ~ subject + cond + electrode, data = P600, FUN = mean)

P600$subject <- factor(P600$subject)
P600$cond <- factor(P600$cond)

ezANOVA(data = P600,
        dv = volt,
        wid = subject,
        within = cond,
        type = 3)

ezStats(data = P600,
        dv = volt,
        wid = subject,
        within = cond,
        type = 3)

P600 <- aggregate(volt ~ subject + cond, data = P600, FUN = mean)

pairwise.t.test(P600$volt, P600$cond, paired = TRUE,  p.adjust.method = "bonf")
pairwise.t.test(P600$volt, P600$cond, paired = TRUE,  p.adjust.method = "none")

t.test(P600$volt[P600$cond == "EXP "], P600$volt[P600$cond == "USP "], paired = TRUE)
t.test(P600$volt[P600$cond == "EXP "], P600$volt[P600$cond == "ANOM"], paired = TRUE)
t.test(P600$volt[P600$cond == "USP "], P600$volt[P600$cond == "ANOM"], paired = TRUE)

by(P600$volt, list(P600$cond), stat.desc, basic = FALSE)