| seizure {flexmix} | R Documentation |
Data from a clinical trial where the effect of intravenous gamma-globulin on suppression of epileptic seizures is studied. There are daily observations for a period of 140 days on one patient, where the first 27 days are a baseline period without treatment, the remaining 113 days are the treatment period.
data("seizure")
A data frame with 140 observations on the following 4 variables.
No and YesP. Wang, M. Puterman, I. Cockburn, and N. Le (1996): Mixed poisson regression models with covariate dependent rates. Biometrics 52, pages 381-400.
B. Gruen and F. Leisch (2004): Bootstrapping finite mixture models. In J. Antoch, editor, Compstat 2004 - Proceedings in Computational Statistics, pages 1115-1122. Physika Verlag, Heidelberg, Germany, ISBN 3-7908-1554-3.
data("seizure")
plot(Seizures/Hours~Day, col=as.integer(Treatment),
pch=as.integer(Treatment), data=seizure)
abline(v=27.5, lty=2, col="grey")
legend(140, 9, c("Baseline", "Treatment"),
pch=1:2, col=1:2, xjust=1, yjust=1)
set.seed(123)
## The model presented in the Wang et al paper: two components for
## "good" and "bad" days, respectively, each a Poisson GLM with hours of
## parental observation as offset
seizMix <- flexmix(Seizures~Treatment*log(Day),
data=seizure, k=2,
model=FLXMRglm(family="poisson", offset=log(seizure$Hours)))
summary(seizMix)
summary(refit(seizMix))
matplot(seizure$Day, fitted(seizMix)/seizure$Hours, type="l",
add=TRUE, col=3:4)