getDesignMatrix: Computes a design matrix from factors and interactions
In glmmBUGS: Generalised Linear Mixed Models with BUGS and JAGS

Description Usage Arguments Details Value Author(s) See Also Examples

Converts all factors and interactions to indicator variables, suitable for passing to WinBUGS.

1	getDesignMatrix(formula, data, effects = NULL)

`formula`	A `formula` object specifying the fixed effects for the model
`data`	A data frame containing the covariates and factors for random effects
`effects`	A vector of character strings containing the grouping levels, from most general to most specific

The most populous level of a factor is made the baseline.

A matrix containing the covariates, the response(s), and the random effect factors. Also attributes

`covariates`	A list giving the covariates which apply at each level, suitable for passing to `winBugsRaggedArray`
`response`	A vector of character strings giving the responses

Patrick Brown

winBugsRaggedArray, glmmBUGS

library(nlme)
data(Muscle)
muscleDesign = getDesignMatrix(conc ~ length, data=Muscle, effects="Strip" )
attributes(muscleDesign)$covariates
attributes(muscleDesign)$response