*data from Gregoriou, O, Vitoratos, N, 
Papadias, C, Konidaris, S, Gargaropoulos,
A, Rizos, D. Pregnancy rates in gonadotrophin 
stimulated cycles with timed intercourse or 
intrauterine insemination for the treatment
of male subfertility, 
Eur J Obstet Gynecol Reprod Biol 1996; 64: 213-216.


#Model involving period effect only

model
	{
	   for( i in 1 : N1 ) {
	   	outcome1[i] ~ dbern(p1[i])  
		   logit(p1[i]) <- intercept+pi*period1[i]+b[i]
		
		
		
		b[i] ~ dnorm(0, beta)
	   }
	
	
	
	for( i in 1 : N2){
		outcome2[i] ~ dbern(p2[i])
		logit(p2[i]) <- intercept+pi*period2[i]+b[i]
		 }
	
	
	
	  sigma<- 1/sqrt(beta) 
	   intercept ~ dnorm(0,1.0E-3)
	   pi ~ dnorm(0,1.0E-3)
	   beta~ dgamma(1,1.0E-3)
	  log.sigma<- log(sigma)
	   
	   
	}	
	
	list(outcome1 =c(0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 1, 1, 1, 1, 1, 1, 1,1,1,1,1,1) ,
		
	
	period1 =c(0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0),
		
		
		outcome2 =c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 1, 1, 1, 1,1,1,1,1)  ,
		
		period2=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),
		
		
		
		N1 = 62, N2=50),
		
		
		
		list(intercept=-1,pi=1,beta=10,b=c(0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0)) 
		
		
		
		
	list(intercept=-4,pi=4,beta=15,b=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,1)) 








*********************************************************************
*********************************************************************
#The model involving both treatment and period effect

model
	{
	   for( i in 1 : N1 ) {
	   	outcome1[i] ~ dbern(p1[i])  
		   logit(p1[i]) <- intercept+tau*treatment1[i]+pi*period1[i]+b[i]
		
		
		
		b[i] ~ dnorm(0, beta)
	   }
	
	
	
	for( i in 1 : N2){
		outcome2[i] ~ dbern(p2[i])
		logit(p2[i]) <- intercept+tau*treatment2[i]+pi*period2[i]+b[i]
		 }
	
	
	
	  sigma<- 1/sqrt(beta) 
	   intercept ~ dnorm(0,1.0E-3)
	   tau ~ dnorm(0,1.0E-3)
	   pi ~ dnorm(0,1.0E-3)
	   beta~ dgamma(1,1.0E-3)
	  log.sigma<- log(sigma)
	   
	   
	}	
	
	list(outcome1 =c(0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 1, 1, 1, 1, 1, 1, 1,1,1,1,1,1) ,
		
	treatment1=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1)	,
	
	period1 =c(0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0),
		
		
		outcome2 =c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 1, 1, 1, 1,1,1,1,1)  ,
		
		period2=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),
		
		treatment2=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0),
		
		N1 = 62, N2=50),
		
		
		
		list(intercept=-1,tau=-1,pi=1,beta=10,b=c(0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0)) 
		
		
		
		
	list(intercept=-4,tau=-4,pi=4,beta=15,b=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,1)) 








*********************************************************************
*********************************************************************
#The null Model

model
	{
	   for( i in 1 : N1 ) {
	   	outcome1[i] ~ dbern(p1[i])  
		   logit(p1[i]) <- intercept+b[i]
		
		
		
		b[i] ~ dnorm(0, beta)
	   }
	
	
	
	for( i in 1 : N2){
		outcome2[i] ~ dbern(p2[i])
		logit(p2[i]) <- intercept+b[i]
		 }
	
	
	
	  sigma<- 1/sqrt(beta) 
	   intercept ~ dnorm(0,1.0E-3)
	   beta ~ dgamma(1,1.0E-3)
	  log.sigma<- log(sigma)
	   
	   
	}	
	
	list(outcome1 =c(0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 1, 1, 1, 1, 1, 1, 1,1,1,1,1,1) ,
		

	
	
		
		outcome2 =c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 1, 1, 1, 1,1,1,1,1)  ,
		
		
		

		
		N1 = 62, N2=50),
		
		
		
		list(intercept=-1,beta=10,b=c(0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0)) 
		
		
		
		
	list(intercept=-4,beta=15,b=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,1)) 






*****************************************************************************
*****************************************************************************
#The model involving treatment only

model
	{
	   for( i in 1 : N1 ) {
	   	outcome1[i] ~ dbern(p1[i])  
		   logit(p1[i]) <- intercept+tau*treatment1[i]+b[i]
		
		
		
		b[i] ~ dnorm(0, beta)
	   }
	
	
	
	for( i in 1 : N2){
		outcome2[i] ~ dbern(p2[i])
		logit(p2[i]) <- intercept+tau*treatment2[i]+b[i]
		 }
	
	
	
	  sigma<- 1/sqrt(beta) 
	   intercept ~ dnorm(0,1.0E-3)
	   tau ~ dnorm(0,1.0E-3)
	   beta ~ dgamma(1,1.0E-3)
	  log.sigma<- log(sigma)
	   
	   
	}	
	
	list(outcome1 =c(0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 1, 1, 1, 1, 1, 1, 1,1,1,1,1,1) ,
		
	treatment1=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1)	,
	
	
		
		
		outcome2 =c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 1, 1, 1, 1,1,1,1,1)  ,
		
		
		
		treatment2=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0),
		
		N1 = 62, N2=50),
		
		
		
		list(intercept=-1,tau=-1,beta=10,b=c(0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,0)) 
		
		
		
		
	list(intercept=-4,tau=-4,beta=15,b=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0 ,0 ,0, 0, 0 ,0, 0, 0, 0, 0,0, 0, 0 ,0, 0, 0, 0, 0, 0 ,0 ,0, 0, 0, 0, 0, 0,0,0,0,0,0,0,0,0,1))