oxboys.saemix: Heights of Boys in Oxford

In saemixdevelopment/saemix: Stochastic Approximation Expectation Maximization (SAEM) Algorithm

Description

The oxboys.saemix data frame has 234 rows and 4 columns.

Usage

oxboys.saemix

Format

This data frame contains the following columns:

Subject:

an ordered factor giving a unique identifier for each boy in the experiment

age:

a numeric vector giving the standardized age (dimensionless)

height:

a numeric vector giving the height of the boy (cm)

Occasion:

an ordered factor - the result of converting 'age' from a continuous variable to a count so these slightly unbalanced data can be analyzed as balanced.

Details

These data are described in Goldstein (1987) as data on the height of a selection of boys from Oxford, England versus a standardized age. The dataset can be found in the package nlme.

We use an linear model for this data: y_ij = Base_i + slope_i x_ij +epsilon_ij

Source

Pinheiro, J. C. and Bates, D. M. (2000), _Mixed-Effects Models in S and S-PLUS_, Springer, New York. (Appendix A.19)

Examples

 

data(oxboys.saemix)
saemix.data<-saemixData(name.data=oxboys.saemix,header=TRUE,
  name.group=c("Subject"),name.predictors=c("age"),name.response=c("height"),
  units=list(x="yr",y="cm"))

# plot the data
plot(saemix.data)

growth.linear<-function(psi,id,xidep) {
# input:
#   psi : matrix of parameters (2 columns, base and slope)
#   id : vector of indices 
#   xidep : dependent variables (same nb of rows as length of id)
# returns:
#   a vector of predictions of length equal to length of id
  x<-xidep[,1]
  base<-psi[id,1]
  slope<-psi[id,2]
  f<-base+slope*x
  return(f)
}
saemix.model<-saemixModel(model=growth.linear,description="Linear model",
  psi0=matrix(c(140,1),ncol=2,byrow=TRUE,dimnames=list(NULL,c("base","slope"))),
  transform.par=c(1,0),covariance.model=matrix(c(1,1,1,1),ncol=2,byrow=TRUE), 
  error.model="constant")

saemix.options<-list(algorithms=c(1,1,1),nb.chains=1,seed=201004,
  save=FALSE,save.graphs=FALSE)

# Not run (strict time constraints for CRAN)
# saemix.fit<-saemix(saemix.model,saemix.data,saemix.options)

saemixdevelopment/saemix documentation built on May 27, 2020, 1:56 p.m.