Salm: extra - Poisson variation in dose - response study
Breslow (1984) analyses some mutagenicity assay data (shown below) on salmonella in which three plates have been processed at each dose
i of quinoline and the number of revertant colonies of TA98 Salmonella measured. A certain dose-response curve is suggested by theory.
![[salm1]](salm1.bmp)
This is assumed to be a random effects Poisson model allowing for over-dispersion. Let x
i be the dose on the plates
i1,
i2 and
i3. Then we assume
y
ij ~ Poisson(
μij)
log(
μij) =
α +
β log(x
i + 10) +
γx
i +
λij λij ~ Normal(0,
τ)
α , β , γ , τ are given independent ``noninformative'' priors. The appropriate graph is shown
Graphical model for salm example
![[salm2]](salm2.bmp)
BUGS language for salm example
model
{
for( i in 1 : doses ) {
for( j in 1 : plates ) {
y[i , j] ~ dpois(mu[i , j])
log(mu[i , j]) <- alpha + beta * log(x[i] + 10) +
gamma * x[i] / 1000 + lambda[i , j]
lambda[i , j] ~ dnorm(0.0, tau)
}
}
alpha ~ dnorm(0.0,1.0E-6)
beta ~ dnorm(0.0,1.0E-6)
gamma ~ dnorm(0.0,1.0E-6)
tau ~ dgamma(0.001, 0.001)
sigma <- 1 / sqrt(tau)
}
Data
list(doses = 6, plates = 3,
y = structure(.Data = c(15,21,29,16,18,21,16,26,33,27,41,60,33,38,41,20,27,42),
.Dim = c(6, 3)),
x = c(0, 10, 33, 100, 333, 1000))
Inits for chain 1
list(alpha = 0, beta = 0, gamma = 0, tau = 0.1)
Inits for chain 2
list(alpha = 1.0, beta = 1.0, gamma = 0.01, tau = 1.0)
Results
![[salm3]](salm3.bmp)
These estimates can be compared with the quasi-likelihood estimates of Breslow (1984) who reported
α = 2.203 +/- 0.363,
β = 0.311 +/- 0.099,
γ = -9.74E-4 +/- 4.37E-4,
σ = 0.268