seizure {flexmix} | R Documentation |
Data from a clinical trial where the effect of intravenous gamma-globulin on suppression of epileptic seizures is studied. Daily observations for a period of 140 days on one patient are given, 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.
A numeric vector, daily counts of epileptic seizures.
A numeric vector, hours of daily parental observation.
A factor with levels No
and Yes
.
A numeric vector.
P. 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)