# Edps 589
# Fall 2018
# c.j.anderson
#
# Model building:  Wichens/Olzak signal detection data and using graphs to guide modeling
library(vcd)

#setwd("C:\\Users\\cja\\Dropbox\\edps 589\\7Model_building")
setwd("D:\\Dropbox\\edps 589\\7Model_building")

sd <- read.table("wickens_olzak_data.txt",header=T) 
head(sd)


# H = whether high is present
# L = whether low is present
# Hres = response regarding high
# Lres = response regarding low

sd$Hres <- as.factor(sd$Hres)
sd$Lres <- as.factor(sd$Lres)


## Random responding
summary( mod1 <- glm(count ~ H + L + H*L + Hres + Lres, data=sd, family=poisson) )
1-pchisq(mod1$deviance,mod1$df.residual)


## Detectable signals 
summary( mod2 <- glm(count ~ H + L + H*L + Hres + Lres + H*Hres + L*Lres, data=sd, family=poisson) )
1
-pchisq(mod2$deviance,mod2$df.residual)

## Association with unrelated signals
summary( mod3 <- glm(count ~ H + L + H*L 
                    + Hres + Lres + H*Hres  
					+ L*Lres + H*Lres 
					+ L*Hres + H*L*Lres + H*L*Hres, data=sd, family=poisson) )
1-pchisq(mod3$deviance,mod3$df.residual)


## Response - Response association
summary( mod4 <- glm(count ~ H + L + H*L 
                    + Hres + Lres 
					+ H*Hres + L*Lres + Lres*Hres, data=sd, family=poisson) )
1-pchisq(mod4$deviance,mod4$df.residual)


## Homegenous assocation (All 2-way)
summary( mod5 <- glm(count ~ H + L + H*L 
                    + Hres + Lres 
					+ H*Hres + L*Lres + H*Lres + L*Hres + Lres*Hres, data=sd, family=poisson) )
1-pchisq(mod5deviance,mod5$df.residual)


## Final model
summary( mod6 <- glm(count ~ H + L + H*L 
                    + Hres + Lres 
					+ H*Hres + L*Lres + H*Lres + L*Hres + Lres*Hres 
					+ H*L*Lres, data=sd, family=poisson) )
1-pchisq(mod6$deviance,mod6$df.residual)