epilepsy {robustbase} | R Documentation |
Epilepsy Attacks Data Set
Description
Data from a clinical trial of 59 patients with epilepsy (Breslow, 1996) in order to illustrate diagnostic techniques in Poisson regression.
Usage
data(epilepsy, package="robustbase")
Format
A data frame with 59 observations on the following 11 variables.
ID
Patient identification number
Y1
Number of epilepsy attacks patients have during the first follow-up period
Y2
Number of epilepsy attacks patients have during the second follow-up period
Y3
Number of epilepsy attacks patients have during the third follow-up period
Y4
Number of epilepsy attacks patients have during the forth follow-up period
Base
Number of epileptic attacks recorded during 8 week period prior to randomization
Age
Age of the patients
Trt
a factor with levels
placebo
progabide
indicating whether the anti-epilepsy drug Progabide has been applied or notYsum
Total number of epilepsy attacks patients have during the four follow-up periods
Age10
Age of the patients devided by 10
Base4
Variable
Base
devided by 4
Details
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.
Source
Thall, P.F. and Vail S.C. (1990) Some covariance models for longitudinal count data with overdispersion. Biometrics 46, 657–671.
References
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.
Examples
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)