Nothing
model.binary.hom.eqcor <- function(prior.type = "unif", rank.prob = TRUE){
if(prior.type == "unif" & rank.prob){
modelstring<-"
model{
for(i in 1:len){
p[i] <- phi(mu[t[i]] + vi[s[i], t[i]])
r[i] ~ dbin(p[i], totaln[i])
rhat[i] <- p[i]*totaln[i]
dev[i] <- 2*(r[i]*(log(r[i]) - log(rhat[i])) +
(totaln[i] - r[i])*(log(totaln[i] - r[i]) - log(totaln[i] - rhat[i])))
}
totresdev <- sum(dev[])
for(j in 1:nstudy){
vi[j, 1:ntrt] ~ dmnorm(zeros[1:ntrt], T[1:ntrt, 1:ntrt])
}
for(j in 1:ntrt){
AR[j] <- phi(mu[j]/sqrt(1 + pow(sigma, 2)))
mu[j] ~ dnorm(0, 0.001)
}
sigma ~ dunif(0.0001, c)
for(j in 1:ntrt){
for(k in 1:ntrt){
T[j,k] <- 1/sigma^2*ifelse(j == k, diag, offdiag)
}
}
diag <- (1 + (ntrt - 2)*rho)/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2)
offdiag <- (-rho/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2))
rho ~ dunif(-1/(ntrt - 1), 0.9999)
for(j in 1:ntrt){
for(k in 1:ntrt){
LRR[j,k] <- log(RR[j,k])
LOR[j,k] <- log(OR[j,k])
RR[j,k] <- AR[j]/AR[k]
RD[j,k] <- AR[j] - AR[k]
OR[j,k] <- AR[j]/(1 - AR[j])/AR[k]*(1 - AR[k])
}
}
rk[1:ntrt] <- (ntrt + 1 - rank(AR[]))*ifelse(higher.better, 1, 0) + (rank(AR[]))*ifelse(higher.better, 0, 1)
for(i in 1:ntrt){
rank.prob[1:ntrt, i] <- equals(rk[], i)
}
}
"
}
if(prior.type == "unif" & !rank.prob){
modelstring<-"
model{
for(i in 1:len){
p[i] <- phi(mu[t[i]] + vi[s[i], t[i]])
r[i] ~ dbin(p[i], totaln[i])
rhat[i] <- p[i]*totaln[i]
dev[i] <- 2*(r[i]*(log(r[i]) - log(rhat[i])) +
(totaln[i] - r[i])*(log(totaln[i] - r[i]) - log(totaln[i] - rhat[i])))
}
totresdev <- sum(dev[])
for(j in 1:nstudy){
vi[j, 1:ntrt] ~ dmnorm(zeros[1:ntrt], T[1:ntrt, 1:ntrt])
}
for(j in 1:ntrt){
AR[j] <- phi(mu[j]/sqrt(1 + pow(sigma, 2)))
mu[j] ~ dnorm(0, 0.001)
}
sigma ~ dunif(0.0001, c)
for(j in 1:ntrt){
for(k in 1:ntrt){
T[j,k] <- 1/sigma^2*ifelse(j == k, diag, offdiag)
}
}
diag <- (1 + (ntrt - 2)*rho)/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2)
offdiag <- (-rho/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2))
rho ~ dunif(-1/(ntrt - 1), 0.9999)
for(j in 1:ntrt){
for(k in 1:ntrt){
LRR[j,k] <- log(RR[j,k])
LOR[j,k] <- log(OR[j,k])
RR[j,k] <- AR[j]/AR[k]
RD[j,k] <- AR[j] - AR[k]
OR[j,k] <- AR[j]/(1 - AR[j])/AR[k]*(1 - AR[k])
}
}
}
"
}
if(prior.type == "invgamma" & rank.prob){
modelstring<-"
model{
for(i in 1:len){
p[i] <- phi(mu[t[i]] + vi[s[i], t[i]])
r[i] ~ dbin(p[i], totaln[i])
rhat[i] <- p[i]*totaln[i]
dev[i] <- 2*(r[i]*(log(r[i]) - log(rhat[i])) +
(totaln[i] - r[i])*(log(totaln[i] - r[i]) - log(totaln[i] - rhat[i])))
}
totresdev <- sum(dev[])
for(j in 1:nstudy){
vi[j, 1:ntrt] ~ dmnorm(zeros[1:ntrt], T[1:ntrt, 1:ntrt])
}
for(j in 1:ntrt){
AR[j] <- phi(mu[j]/sqrt(1 + pow(sigma, 2)))
mu[j] ~ dnorm(0, 0.001)
}
sigma <- 1/sqrt(inv.sig.sq)
inv.sig.sq ~ dgamma(a, b)
for(j in 1:ntrt){
for(k in 1:ntrt){
T[j,k] <- 1/sigma^2*ifelse(j == k, diag, offdiag)
}
}
diag <- (1 + (ntrt - 2)*rho)/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2)
offdiag <- (-rho/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2))
rho ~ dunif(-1/(ntrt - 1), 0.9999)
for(j in 1:ntrt){
for(k in 1:ntrt){
LRR[j,k] <- log(RR[j,k])
LOR[j,k] <- log(OR[j,k])
RR[j,k] <- AR[j]/AR[k]
RD[j,k] <- AR[j] - AR[k]
OR[j,k] <- AR[j]/(1 - AR[j])/AR[k]*(1 - AR[k])
}
}
rk[1:ntrt] <- (ntrt + 1 - rank(AR[]))*ifelse(higher.better, 1, 0) + (rank(AR[]))*ifelse(higher.better, 0, 1)
for(i in 1:ntrt){
rank.prob[1:ntrt, i] <- equals(rk[], i)
}
}
"
}
if(prior.type == "invgamma" & !rank.prob){
modelstring<-"
model{
for(i in 1:len){
p[i] <- phi(mu[t[i]] + vi[s[i], t[i]])
r[i] ~ dbin(p[i], totaln[i])
rhat[i] <- p[i]*totaln[i]
dev[i] <- 2*(r[i]*(log(r[i]) - log(rhat[i])) +
(totaln[i] - r[i])*(log(totaln[i] - r[i]) - log(totaln[i] - rhat[i])))
}
totresdev <- sum(dev[])
for(j in 1:nstudy){
vi[j,1:ntrt] ~ dmnorm(zeros[1:ntrt], T[1:ntrt, 1:ntrt])
}
for(j in 1:ntrt){
AR[j] <- phi(mu[j]/sqrt(1 + pow(sigma, 2)))
mu[j] ~ dnorm(0, 0.001)
}
sigma <- 1/sqrt(inv.sig.sq)
inv.sig.sq ~ dgamma(a, b)
for(j in 1:ntrt){
for(k in 1:ntrt){
T[j,k] <- 1/sigma^2*ifelse(j == k, diag, offdiag)
}
}
diag <- (1 + (ntrt - 2)*rho)/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2)
offdiag <- (-rho/(1 + (ntrt - 2)*rho - (ntrt - 1)*rho^2))
rho ~ dunif(-1/(ntrt - 1), 0.9999)
for(j in 1:ntrt){
for(k in 1:ntrt){
LRR[j,k] <- log(RR[j,k])
LOR[j,k] <- log(OR[j,k])
RR[j,k] <- AR[j]/AR[k]
RD[j,k] <- AR[j] - AR[k]
OR[j,k] <- AR[j]/(1 - AR[j])/AR[k]*(1 - AR[k])
}
}
}
"
}
if(!is.element(prior.type, c("unif", "invgamma"))){
stop("specified prior type is wrong.")
}
return(modelstring)
}
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