Data from a clinical trial of 59 patients with epilepsy (Breslow, 1996) in order to illustrate diagnostic techniques in Poisson regression.
A data frame with 59 observations on the following 11 variables.
Patient identification number
Number of epilepsy attacks patients have during the first follow-up period
Number of epilepsy attacks patients have during the second follow-up period
Number of epilepsy attacks patients have during the third follow-up period
Number of epilepsy attacks patients have during the forth follow-up period
Number of epileptic attacks recorded during 8 week period prior to randomization
Age of the patients
a factor with levels
progabide indicating whether the anti-epilepsy
drug Progabide has been applied or not
Total number of epilepsy attacks patients have during the four follow-up periods
Age of the patients devided by 10
Base devided by 4
Thall and Vail reported data from a clinical trial of 59 patients with epilepsy, 31 of whom were randomized to receive the anti-epilepsy drug Progabide and 28 of whom received a placebo. Baseline data consisted of the patient's age and the number of epileptic seizures recorded during 8 week period prior to randomization. The response consisted of counts of seizures occuring during the four consecutive follow-up periods of two weeks each.
Thall, P.F. and Vail S.C. (1990) Some covariance models for longitudinal count data with overdispersion. Biometrics 46, 657–671.
Diggle, P.J., Liang, K.Y., and Zeger, S.L. (1994) Analysis of Longitudinal Data; Clarendon Press.
Breslow N. E. (1996) Generalized linear models: Checking assumptions and strengthening conclusions. Statistica Applicata 8, 23–41.
1 2 3 4 5 6 7 8 9 10 11 12
data(epilepsy) str(epilepsy) pairs(epilepsy[,c("Ysum","Base4","Trt","Age10")]) Efit1 <- glm(Ysum ~ Age10 + Base4*Trt, family=poisson, data=epilepsy) summary(Efit1) ## Robust Fit : Efit2 <- glmrob(Ysum ~ Age10 + Base4*Trt, family=poisson, data=epilepsy, method = "Mqle", tcc=1.2, maxit=100) summary(Efit2)