epil {MASS} | R Documentation |

## Seizure Counts for Epileptics

### Description

Thall and Vail (1990) give a data set on two-week seizure counts for
59 epileptics. The number of seizures was recorded for a baseline
period of 8 weeks, and then patients were randomly assigned to a
treatment group or a control group. Counts were then recorded for
four successive two-week periods. The subject's age is the only
covariate.

### Usage

epil

### Format

This data frame has 236 rows and the following 9 columns:

`y`

- The count for the 2-week period.
`trt`

- The treatment,
`"placebo"`

or `"progabide"`

.
`base`

- The counts in the baseline 8-week period.
`age`

- The subject's age, in years.
`V4`

`0/1`

indicator variable of period 4.
`subject`

- The subject number, 1 to 59.
`period`

- The period, 1 to 4.
`lbase`

- The log-counts for the baseline period, centred to have zero mean.
`lage`

- The log-ages, centred to have zero mean.

### Source

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

### References

Venables, W. N. and Ripley, B. D. (2002)
*Modern Applied Statistics with S.* Fourth Edition. Springer.

### Examples

summary(glm(y ~ lbase*trt + lage + V4, family = poisson,
data = epil), cor = FALSE)
epil2 <- epil[epil$period == 1, ]
epil2["period"] <- rep(0, 59); epil2["y"] <- epil2["base"]
epil["time"] <- 1; epil2["time"] <- 4
epil2 <- rbind(epil, epil2)
epil2$pred <- unclass(epil2$trt) * (epil2$period > 0)
epil2$subject <- factor(epil2$subject)
epil3 <- aggregate(epil2, list(epil2$subject, epil2$period > 0),
function(x) if(is.numeric(x)) sum(x) else x[1])
epil3$pred <- factor(epil3$pred,
labels = c("base", "placebo", "drug"))
contrasts(epil3$pred) <- structure(contr.sdif(3),
dimnames = list(NULL, c("placebo-base", "drug-placebo")))
summary(glm(y ~ pred + factor(subject) + offset(log(time)),
family = poisson, data = epil3), cor = FALSE)
summary(glmmPQL(y ~ lbase*trt + lage + V4,
random = ~ 1 | subject,
family = poisson, data = epil))
summary(glmmPQL(y ~ pred, random = ~1 | subject,
family = poisson, data = epil3))

[Package

*MASS* version 7.2-23

Index]