# epilepsy.saemix: Epilepsy count data In saemix: Stochastic Approximation Expectation Maximization (SAEM) Algorithm

 epilepsy.saemix R Documentation

## Epilepsy count data

### Description

The epilepsy data from Thall and Vail (1990), available from the MASS package, records 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. See the documentation for epil in the MASS package for details on the dataset.

### Source

MASS package in R

### References

P Thall, S Vail (1990). Some covariance models for longitudinal count data with overdispersion. Biometrics 46(3):657-71.

### Examples

```# You need to have MASS installed to successfully run this example
if (requireNamespace("MASS")) {

epilepsy<-MASS::epil
saemix.data<-saemixData(name.data=epilepsy, name.group=c("subject"),
name.predictors=c("period","y"),name.response=c("y"),
name.covariates=c("trt","base", "age"), units=list(x="2-week",y="",covariates=c("","","yr")))
## Poisson model with one parameter
countPoi<-function(psi,id,xidep) {
y<-xidep[,2]
lambda<-psi[id,1]
logp <- -lambda + y*log(lambda) - log(factorial(y))
return(logp)
}
saemix.model<-saemixModel(model=countPoi,description="Count model Poisson",modeltype="likelihood",
psi0=matrix(c(0.5),ncol=1,byrow=TRUE,dimnames=list(NULL, c("lambda"))), transform.par=c(1))

saemix.options<-list(seed=632545,save=FALSE,save.graphs=FALSE, displayProgress=FALSE)
poisson.fit<-saemix(saemix.model,saemix.data,saemix.options)

}

```

saemix documentation built on Aug. 5, 2022, 5:25 p.m.