getwd()

setwd("C:/Users/Sheri Moinamin/Desktop")

#Read data

CIT=read.csv("CIT.csv")

# View column names

colnames(CIT) 

#Dependent variable is the count of occurrences, which is CITCount

#Complete Independence Poisson regression

CI=glm(CITCount~(FamilyHxBipolar + FamilyHxDepression + CITSuccess), data=CIT, family=poisson)

summary(CI)

# Joint Independence BD (Bipolar and Depression) Poisson regression 

JImodelBD=glm(CITCount ~ (FamilyHxBipolar + FamilyHxDepression + CITSuccess + FamilyHxBipolar * FamilyHxDepression), data=CIT, family=poisson)

summary(JImodelBD)

#Joint Independence BC (Bipolar and CIT Success) Poisson regression 

JImodelBC=glm(CITCount ~ (FamilyHxBipolar + FamilyHxDepression + CITSuccess + FamilyHxBipolar * CITSuccess), data=CIT, family=poisson)

summary(JImodelBC)

#Joint Independence DC (Depression and CIT Success) Poisson regression

JImodelDC=glm(CITCount ~ (FamilyHxBipolar + FamilyHxDepression + CITSuccess + FamilyHxDepression * CITSuccess), data=CIT, family=poisson)

summary(JImodelDC)

# Full Homogenous Poisson regression model 
# Independent variables are main effects and pairwise variables

homogenous=glm(CITCount ~ (FamilyHxBipolar + FamilyHxDepression + CITSuccess)^2, data=CIT, family=poisson)

summary(homogenous)

# Homogenous Association NoBD model(dropping family history of depression and family history of bipolar)

NoBD=update(homogenous,.~.-(FamilyHxBipolar:FamilyHxDepression))

summary(NoBD) 

# Homogenous Association NoBC model(family history of bipolar and CITSuccess)

NoBC=update(homogenous,.~.-(FamilyHxBipolar:CITSuccess))

summary(NoBC) 

# Homogenous Association NoBC model(family history of depression and CITSuccess)

NoDC=update(homogenous,.~.-(FamilyHxDepression:CITSuccess))

summary(NoDC)

# Record the residual deviance and degrees of freedom for each model 
# Record the model with the smallest increase in residual deviance from the full homogenous model