rm(list=ls(all=TRUE))  # clear all variables
graphics.off()  # clear all graphics
# Visual Search
# Greg Francis
# PSY 626
# 02 October 202

# load full data file
ZCdata<-read.csv(file="ZennerCards.csv",header=TRUE,stringsAsFactors=FALSE)

# load the rethinking library
library(rethinking)

# Dummy variables to indicate actual card type and guessed card type
ZCdata$CardIndex <- coerce_index(ZCdata$ActualCard)  # numbers 1-5 assigned to Card names alphabetically
ZCdata$SelectedCardIndex <- coerce_index(ZCdata$GuessedCard) # numbers 1-5 assigned to Card names alphabetically
		
# All cards and subjects treated the same
ZCmodel1 <- map(
			alist( Score ~ dbinom(1, p), 
			logit(p) <- a,
			a ~ dnorm(0, 10)
			), data= ZCdata ) 
		
print(precis(ZCmodel1))
cat("Finished with ZCmodel1\n")

a=coef(ZCmodel1)["a"]

cat("Probability of correct response: ", logistic(a))

# Different probabilities for different actual cards
ZCmodel2 <- map(
			alist( Score ~ dbinom(1, p), 
			logit(p) <- a[CardIndex],
			a[CardIndex] ~ dnorm(0, 10)
			), data= ZCdata ) 
cat("Finished with ZCmodel2\n")
		
print(precis(ZCmodel2, depth=2))

cat("Probability of correct response: ", logistic(coef(ZCmodel2)))

# Different probabilities for different selected cards
ZCmodel3 <- map(
			alist( Score ~ dbinom(1, p), 
			logit(p) <- a[SelectedCardIndex],
			a[SelectedCardIndex] ~ dnorm(0, 10)
			), data= ZCdata ) 
cat("Finished with ZCmodel3\n")

cat("Probability of correct response: ", logistic(coef(ZCmodel3)))

# Null model (p=0.2)
ZCmodel0 <- map(
			alist( Score ~ dbinom(1, p), 
			logit(p) <- a,
			a ~ dnorm(logit(0.2), 0.001)
			), data= ZCdata ) 
		
print(precis(ZCmodel0))

cat("Finished with ZCmodel0\n")
a=coef(ZCmodel0)["a"]

cat("Probability of correct response: ", logistic(a))



# Different probabilities for different participants
ZCmodel4 <- map(
			alist( Score ~ dbinom(1, p), 
			logit(p) <- a[Participant],
			a[Participant] ~ dnorm(0, 10)
			), data= ZCdata ) 
cat("Finished with ZCmodel4\n")
		
print(precis(ZCmodel4, depth=2))

cat("Probability of correct response: ", logistic(coef(ZCmodel4)))


# Different probabilities for different cards and different participants
ZCmodel5 <- map(
			alist( Score ~ dbinom(1, p), 
			logit(p) <- a[CardIndex] + b[Participant],
			a[CardIndex] ~ dnorm(0, 10),
			b[Participant] ~ dnorm(0, 10)
			), data= ZCdata ) 
cat("Finished with ZCmodel5\n")
		
print(precis(ZCmodel5, depth=2))

aValues5<-c()
for(p in unique(ZCdata$Participant)){
for(p2 in sort(unique(ZCdata$CardIndex))){
	code<-sprintf("b[%d]", p)
	code2<-sprintf("a[%d]", p2)
	aValues5<- c(aValues5, coef(ZCmodel5)[code] + coef(ZCmodel5)[code2])	
}
}

cat("Probability of correct response: ", logistic(aValues5))


# Stupid model

# Different probabilities for different selected cards and different participants
ZCdata$InteractionIndex <- 1+ 5*(ZCdata$SelectedCardIndex-1) + (ZCdata$CardIndex-1)  
ZCmodel6 <- map(
			alist( Score ~ dbinom(1, p), 
			logit(p) <- a[InteractionIndex],
			a[InteractionIndex] ~ dnorm(0, 10)
			), data= ZCdata ) 
cat("Finished with ZCmodel6\n")
		
print(precis(ZCmodel6, depth=2))