R: Epilepsy Attacks Data Set

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 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

### 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)

[Package robustbase version 0.93-6 Index]