print(m1a <- lmer(log(fst_fd) ~  fullcnd + (1 | id) + (1 | id:fullcnd) + (1 | psid), data=dat.sfd), cor=FALSE)
library(lme4)#
library(ggplot2)#
#
rm(list=ls())#
#
data <- read.csv("SPB_taipei20110824.csv", header=TRUE)#
data$fullcnd <- relevel(data$fullcnd, 5)#
#
# SFD : semantic preview significant#
ix.sfd <- which(data$fst_fd == 0 | data$fpnofix > 1)#
dat.sfd <- data[-ix.sfd,]#
dat.sfd$pre_fd.c <- scale(dat.sfd$pre_fd, center=TRUE, scale=FALSE)#
#
tapply(dat.sfd$gd, dat.sfd$fullcnd, mean)#
print(m1 <- lmer(log(fst_fd) ~  fullcnd + (1+fullcnd | id) + (1 | psid), data=dat.sfd), cor=FALSE)#
print(m1a <- lmer(log(fst_fd) ~  fullcnd + (1 | id) + (1 | id:fullcnd) + (1 | psid), data=dat.sfd), cor=FALSE)#
print(m2 <- lmer(log(fst_fd) ~  fullcnd + (1 | id) + (1 | psid), data=dat.sfd), cor=FALSE)#
anova(m2, m1a, m1)
str(dat.sfd)
print(m1a <- lmer(log(fst_fd) ~  fullcnd +  (1 | id/fullcnd) + (1 | psid), data=dat.sfd), cor=FALSE)
rm(list=ls())#
#
data <- read.csv("SPB_taipei20110824.csv", header=TRUE)#
data$id <- factor(data$id)#
data$psid <- factor(data$psid)#
data$fullcnd <- relevel(data$fullcnd, 5)#
#
# SFD : semantic preview significant#
ix.sfd <- which(data$fst_fd == 0 | data$fpnofix > 1)#
dat.sfd <- data[-ix.sfd,]#
dat.sfd$pre_fd.c <- scale(dat.sfd$pre_fd, center=TRUE, scale=FALSE)#
#
tapply(dat.sfd$gd, dat.sfd$fullcnd, mean)#
print(m1 <- lmer(log(fst_fd) ~  fullcnd + (1+fullcnd | id) + (1 | psid), data=dat.sfd), cor=FALSE)#
print(m1a <- lmer(log(fst_fd) ~  fullcnd + (1 | id) + (1 | id:fullcnd) + (1 | psid), data=dat.sfd), cor=FALSE)
setwd('/Users/kliegl/Documents/projects/EyeMoves/SemPrevBenefit_Taipei')
print(m2 <- lmer(log(fst_fd) ~  fullcnd + (1 | id) + (1 | psid), data=dat.sfd), cor=FALSE)#
anova(m2, m1a, m1)
