##### Potsdam Mind Research Repository ######

## This script is part of the publication package for the article:

# Hohenstein, S., & Kliegl, R. (2013).
# Semantic preview benefit during reading.
# Journal of Experimental Psychology: Learning, Memory, and Cognition. 
# http://psycnet.apa.org/doi/10.1037/a0033670


# Sven Hohenstein, 2013


######## Generate statistics and graphs for Experiment 2 #########

rm(list=ls())

# packages
library(lme4)
library(ggplot2)
library(glmmADMB)

# functions
source("remef.v0.6.10.R")



##### Analyses and Plots ######

#### 1) Target

### Fixation durations

# load data
b2 <- readRDS("Exp2.rds")

## main effects
# Gaze duration
summary(mod1_gd <- lmer(b2, formula = log(tar.GD) ~ 1 + PrimeN * CapN + 
                          ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# First-fixation duration
summary(mod1_ffd <- lmer(b2, formula = log(tar.FFD) ~ 1 + PrimeN * CapN + 
                           ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# Single-fixation duration
summary(mod1_sfd <- lmer(b2, formula = log(tar.SFD) ~ 1 + PrimeN * CapN + 
                           ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))

# is the preview effect present for both capitalized and non-capitalized sentences?
# a) Capitalized
print(lmer(b2, formula = log(tar.GD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ), subset = cap == "capitalized"), cor = FALSE) 
print(lmer(b2, formula = log(tar.SFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ), subset = cap == "capitalized"), cor = FALSE) 
print(lmer(b2, formula = log(tar.FFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ), subset = cap == "capitalized"), cor = FALSE) 
# b) Non-capitalized
print(lmer(b2, formula = log(tar.GD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ), subset = cap != "capitalized"), cor = FALSE) 
print(lmer(b2, formula = log(tar.SFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ), subset = cap != "capitalized"), cor = FALSE) 
print(lmer(b2, formula = log(tar.FFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ), subset = cap != "capitalized"), cor = FALSE) 



## influence of distance to pretarget
# Gaze duration
summary(mod_gd_ls <- lmer(b2, 
                          formula = log(tar.GD) ~ PrimeN * CapN * scale(distLast, scale = FALSE) +
                            ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# First-fixation duration
summary(mod_ffd_ls <- lmer(b2, 
                           formula = log(tar.FFD) ~ PrimeN * CapN * scale(distLast, scale = FALSE) +
                             ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# Single-fixation duration
summary(mod_sfd_ls <- lmer(b2, 
                           formula = log(tar.SFD) ~ PrimeN * CapN * scale(distLast, scale = FALSE) +
                             ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))

# analyze GD and SFD separately for both capitalization conditions
# GD
lmer(data=b2, formula = log(tar.GD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ) + distLast + PrimeN:distLast, subset = cap == "capitalized")
lmer(data=b2, formula = log(tar.GD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ) + distLast + PrimeN:distLast, subset = cap == "non-capitalized")
# SFD
lmer(data=b2, formula = log(tar.SFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ) + distLast + PrimeN:distLast, subset = cap == "capitalized")
lmer(data=b2, formula = log(tar.SFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ) + distLast + PrimeN:distLast, subset = cap == "non-capitalized")            
# FFD?
lmer(data=b2, formula = log(tar.FFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ) + distLast + PrimeN:distLast, subset = cap == "capitalized")
lmer(data=b2, formula = log(tar.FFD) ~ 1 + PrimeN + ( 1 | sn ) + ( 1 | id ) + distLast + PrimeN:distLast, subset = cap == "non-capitalized")                 

## Plot (GD)
# remove random effects
b2$DV_mod_gd_ls <- remef(mod_gd_ls, ran = 'all')
ybreaks = seq(170, 330, 20)
xbreaks = seq(1, 8, 1)
p <- ggplot(b2[b2$distLast %in% 1:7,], aes(y = DV_mod_gd_ls, x = distLast, linetype=prime, shape=prime)   )
p <- p + stat_summary(fun.y = mean, geom = "point", size = 2.5)
p <- p + stat_summary(fun.data = "mean_cl_normal", mult = 1, geom = "errorbar", width = 0.2, linetype = 1)
p <- p + scale_y_continuous(name="Target gaze duration [ms]", breaks = log(ybreaks), labels = as.character(ybreaks))
p <- p + scale_linetype("Preview", guide = guide_legend(keywidth = 2)) + scale_shape("Preview")
p <- p + stat_smooth(method = "lm", formula = y ~ poly(x,2), aes(group = prime), size = 1.2, colour = "black", se = FALSE)
p <- p + coord_cartesian(ylim = log(c(min(ybreaks), max(ybreaks))))
p <- p + scale_x_reverse(name = "Launch-site distance [characters]", breaks = xbreaks, labels = as.character(xbreaks))
p <- p + theme_bw()
p <- p + theme(legend.position = "top")
p <- p + facet_wrap(~ cap, nrow = 1)
p <- p + theme(strip.background = element_rect(colour = "darkgrey", fill = "lightgrey", size = .2))
p


## influence of pretarget viewing time
# Gaze duration
summary(mod_gd_pt <- lmer(b2, 
                          formula = log(tar.GD) ~ PrimeN * CapN * scale(log(pretar.GD), scale = FALSE) +
                            ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
summary(lmer(b2, 
             formula = log(tar.GD) ~ PrimeN * CapN * scale(log(pretar.FFD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
summary(lmer(b2, 
             formula = log(tar.GD) ~ PrimeN * CapN * scale(log(pretar.SFD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# First-fixation duration
summary(lmer(b2, 
             formula = log(tar.FFD) ~ PrimeN * CapN * scale(log(pretar.GD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
summary(lmer(b2, 
             formula = log(tar.FFD) ~ PrimeN * CapN * scale(log(pretar.FFD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
summary(lmer(b2, 
             formula = log(tar.FFD) ~ PrimeN * CapN * scale(log(pretar.SFD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# Single-fixation duration
summary(lmer(b2, 
             formula = log(tar.SFD) ~ PrimeN * CapN * scale(log(pretar.GD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
summary(lmer(b2, 
             formula = log(tar.SFD) ~ PrimeN * CapN * scale(log(pretar.FFD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
summary(lmer(b2, 
             formula = log(tar.SFD) ~ PrimeN * CapN * scale(log(pretar.SFD), scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))


# Plot (GD -> GD)
# remove random effects
b2$DV_mod_gd_pt <- remef(mod_gd_pt, ran = 'all')
#
ybreaks = seq(200, 350, 50)
xbreaks = seq(100, 500, 50)
#nsplit <- 10
p <- ggplot(b2, aes(y=DV_mod_gd_pt, x = pretar.GD, linetype=prime, shape=prime)   )
p <- p + scale_y_continuous(name="Target gaze duration [ms]", breaks = log(ybreaks), labels = as.character(ybreaks))
p <- p + scale_linetype("Preview", guide = guide_legend(keywidth = 2)) + scale_shape("Preview")
p <- p + geom_vline(xintercept = exp(mean(log(b2$pretar.GD))), linetype = 5, colour = "darkgrey")
p <- p + stat_smooth(method = "lm", formula = y ~ poly(x,2), aes(group = prime), size = 1.2, colour = "black")
p <- p + coord_cartesian(xlim = exp(quantile(log(b2$pretar.GD), c(0.05, 0.95) )), ylim =log(c(min(ybreaks), max(ybreaks))))
p <- p + scale_x_continuous(name = "Pretarget gaze duration [ms]", breaks =(xbreaks), labels = as.character(xbreaks), trans = "log")
p <- p + theme_bw()
p <- p + theme(legend.position = "top")
p <- p + facet_wrap(~ cap, nrow = 1)
p <- p + theme(strip.background = element_rect(colour = "darkgrey", fill = "lightgrey", size = .2))
p

## test influence of pretarget viewing time (separately for both capitalization conditions)
# with SFD --> SFD
summary(lmer(data=b2, formula = 
               log(tar.SFD) ~ 1 + PrimeN * scale(log(pretar.SFD), scale = FALSE)  + ( 1 | sn ) + ( 1 | id ), subset = cap == "capitalized"))
summary(lmer(data=b2, formula =
               log(tar.SFD) ~ 1 + PrimeN * scale(log(pretar.SFD), scale = FALSE) + ( 1 | sn ) + ( 1 | id ), subset = cap == "non-capitalized"))
# with SFD --> GD
summary(lmer(data=b2, formula =
               log(tar.GD) ~ 1 + PrimeN * scale(log(pretar.SFD), scale = FALSE) + ( 1 | sn ) + ( 1 | id ), subset = cap == "capitalized"))
summary(lmer(data=b2, formula =
               log(tar.GD) ~ 1 + PrimeN * scale(log(pretar.SFD), scale = FALSE) + ( 1 | sn ) + ( 1 | id ), subset = cap == "non-capitalized"))
# with GD --> GD
summary(lmer(data=b2, formula =
               log(tar.GD) ~ 1 + PrimeN * scale(log(pretar.GD), scale = FALSE) + ( 1 | sn ) + ( 1 | id ), subset = cap == "capitalized"))
summary(lmer(data=b2, formula = 
               log(tar.GD) ~ 1 + PrimeN * scale(log(pretar.GD), scale = FALSE) + ( 1 | sn ) + ( 1 | id ), subset = cap == "non-capitalized"))
# with GD --> SFD
summary(lmer(data=b2, formula = 
               log(tar.SFD) ~ 1 + PrimeN * scale(log(pretar.GD), scale = FALSE) + ( 1 | sn ) + ( 1 | id ), subset = cap == "capitalized"))
summary(lmer(data=b2, formula = 
               log(tar.SFD) ~ 1 + PrimeN * scale(log(pretar.GD), scale = FALSE) + ( 1 | sn ) + ( 1 | id ), subset = cap == "non-capitalized"))


## influence of display-change recognition rate
# Gaze duration
summary(lmer(b2, 
             formula = log(tar.GD) ~ PrimeN * CapN * scale(percent, scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# First-fixation duration
summary(lmer(b2, 
             formula = log(tar.FFD) ~ PrimeN * CapN * scale(percent, scale = FALSE) +
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# Single-fixation duration
summary(lmer(b2, 
             formula = log(tar.SFD) ~ PrimeN * CapN * scale(percent, scale = FALSE) + 
               ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))


### Other variables

## Target landing position
summary(lmer(b2, formula = o ~ PrimeN * CapN + ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))

## Target refixation probability
summary(glmmadmb(b2, formula = as.integer(refix) ~ PrimeN * CapN + ( 1 | sn ) + ( 1 | id ), 
                 family = "binomial", link = "logit"))


#### Pretarget

## Fixation duration
# GD
summary(lmer(b2, formula = log(pretar.GD) ~ PrimeN * CapN + ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# FFD
summary(lmer(b2, formula = log(pretar.FFD) ~ PrimeN * CapN + ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))
# SFD
summary(lmer(b2, formula = log(pretar.SFD) ~ PrimeN * CapN + ( 1 | sn ) + ( 1 | id ) + ( 0 + CapN | id )))


### Target skipping

# load data
b7 <- readRDS("Exp2_skip.rds")

## main effects
summary(glmmadmb(b7, formula = as.integer(value) ~ PrimeN * CapN + ( 1 | sn ) + ( 1 | id ), 
                 family = "binomial", link = "logit"))