robustbase (version 0.92-6)

epilepsy: 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)

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 not

Ysum

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

Source

Thall, P.F. and Vail S.C. (1990) Some covariance models for longitudinal count data with overdispersion. Biometrics 46, 657--671.

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.

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)