R/modelNMABinSUCRA.R In esm-ispm-unibe-ch/rankingagreement:

```### Binary model with SUCRA calculation

modelNMABinary.SUCRA <- function ()
{
for (i in 1:ns) {
w[i, 1] <- 0
theta[i, t[i, 1]] <- 0
for (k in 1:na[i]) {
r[i, t[i, k]] ~ dbin(p[i, t[i, k]], n[i, t[i, k]])
}
logit(p[i, t[i, 1]]) <- u[i]
for (k in 2:na[i]) {
logit(p[i, t[i, k]]) <- u[i] + theta[i, t[i, k]]
theta[i, t[i, k]] ~ dnorm(md[i, t[i, k]], precd[i,
t[i, k]])
md[i, t[i, k]] <- mean[i, k] + sw[i, k]
w[i, k] <- (theta[i, t[i, k]] - mean[i, k])
sw[i, k] <- sum(w[i, 1:(k - 1)])/(k - 1)
precd[i, t[i, k]] <- prec * 2 * (k - 1)/k
mean[i, k] <- d[t[i, k]] - d[t[i, 1]]
}
}
for (i in 1:ns) {
u[i] ~ dnorm(0, 0.01)
}
tau ~ dnorm(0, 1) %_% T(0, )
prec <- 1/pow(tau, 2)
tau.sq <- pow(tau, 2)
d[ref] <- 0
for (k in 1:(ref - 1)) {
d[k] ~ dnorm(0, 0.01)
}
for (k in (ref + 1):nt) {
d[k] ~ dnorm(0, 0.01)
}
for (i in 1:(nt - 1)) {
for (j in (i + 1):nt) {
OR[j, i] <- exp(d[j] - d[i])
LOR[j, i] <- d[j] - d[i]
}
}
for (j in 1:(ref - 1)) {
ORref[j] <- exp(d[j] - d[ref])
LORref[j] <- d[j] - d[ref]
}
for (j in (ref + 1):nt) {
ORref[j] <- exp(d[j] - d[ref])
LORref[j] <- d[j] - d[ref]
}
order[1:nt] <- rank(d[1:nt])
for (k in 1:nt) {
most.effective[k] <- equals(order[k], 1)
for (j in 1:nt) {
effectiveness[k, j] <- equals(order[k], j)
}
}
for (k in 1:nt) {
for (j in 1:nt) {
cumeffectiveness[k, j] <- sum(effectiveness[k, 1:j])
}
}
for (k in 1:nt) {
SUCRA[k] <- sum(cumeffectiveness[k, 1:(nt - 1)])/(nt -
1)
}
}
```
esm-ispm-unibe-ch/rankingagreement documentation built on July 7, 2020, 2:18 p.m.