Thanks to Nicky Welton and Andrew Thomas for their help.
There was an error in my programm : I should write mean(e[,t[i,k]]) rather
than mean(e[,t[,k]]). As WinBUGS can't find the mean of a vector when there
are missing values, I have worked out the covariate means outside of
WinBUGS, and then read them in as a vector in my first data list.
Thanks again
Stéphanie
-----Message d'origine-----
De : (The BUGS software mailing list) [mailto:[log in to unmask]]De la
part de Stephanie Payet
Envoyé : mercredi 19 juillet 2006 09:57
À : [log in to unmask]
Objet : MTC and meta-regression
Dear BUGS users,
I tried to fit a mixed treatment comparisons model together with a
meta-regression model. I have to compare 10 treatments, I dispose of 16
trials and I'd like to adjust for a variable representing the percentage of
patients with severe disease in each arm (e).
I tried the following programm (the core programm is based on the one given
on the hsrc website : full random effect model) :
model {
for (i in 1:ns) {
w[i,1] <- 0
delta[i,t[i,1]] <- 0
mu[i] ~ dnorm(0,.0001)
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,k]]) <- mu[i] + delta[i,t[i,k]] + beta*(e[i,t[i,k]] -
mean(e[,t[,k]]))
}
for (k in 2:na[i]) {
delta[i,t[i,k]] ~ dnorm(md[i,t[i,k]],taud[i,t[i,k]])
md[i,t[i,k]] <- d[t[i,k]] - d[t[i,1]] + sw[i,k]
taud[i,t[i,k]] <- tau *2*(k-1)/k
w[i,k] <- (delta[i,t[i,k]] - d[t[i,k]] + d[t[i,1]])
sw[i,k] <- sum(w[i,1:k-1])/(k-1)
}
}
d[1] <- 0
for (k in 2:nt) { d[k] ~ dnorm(0,.0001) }
beta ~ dnorm(0.0,1.0E-6)
sd ~ dunif(0,2)
tau <- 1/pow(sd,2)
for (i in 1:ns) { mu1[i] <- mu[i]*equals(t[i,1],1) }
for (k in 1:nt) { logit(T[k]) <- sum(mu1[])/7 + d[k] }
for (c in 1:(nt-1)) {
for (k in (c+1):nt) { or[c,k] <- exp(d[k] - d[c]) }
}
}
data are under the form :
list(nt=10,ns=16)
r[,1] n[,1] e[,1] r[,2] n[,2] e[,2] .... t[,1] t[,2] t[,3] na[]
the model doesn't compile and I don't know how to interprete the errors
Any help would be very appreciated
Thanks
Stéphanie
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