winBugsRaggedArray: Ragged Arrays for multilevel models in BUGS
In glmmBUGS: Generalised Linear Mixed Models with BUGS and JAGS

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

Suitable for unbalanced data.

winBugsRaggedArray(data, effects = names(data)[-length(names(data))], 
covariates = NULL, observations = names(data)[length(names(data))], 
returnData = FALSE,
prefix=NULL, reparam=FALSE)

`data`	A data frame containing the response, covariates, and group membership.
`effects`	A vector of character strings containing the grouping levels, from most general to most specific. Defaults to the column names of data, excluding the last column.
`covariates`	A list with names corresponding to effects and each element being a vector of covariates applicable at that level
`observations`	A character string giving the column of observations, or a vector where the first element is the observations and the remaning are offsets.
`returnData`	If true, returns the re-ordered data frame as well as the data frame
`prefix`	Character string to be appended to variable names
`reparam`	Vector of effect names, reparametrize the intercept by subtracting the mean of covariates at this level.

This funciton creates a list of data suitable for passing to the bugs function, suitable for implimentation as a ragged array. The output can be passed to getStartingValues to manipulate the output from glmmPQLstrings, and to restoreParams to restore the original parametrisation from bugs output.

A list with the following components

`Nxx`	The number of levels in the most general groupping
`Syy`	Indexing sequences, one for each level. If yy is level n, level n+1 has elements Syy[1] to Syy[2]-1 belonging to the first category of level n.
`Xyy`	Matrix or vector of covariates belonging to level yy
	vector of observations.

Patrick Brown, patrick.brown@utoronto.ca

"Handling unbalanced datasets" in the "Tricks: Advanced Use of the BUGS Language" section of the bugs manual, at http://www.openbugs.net/Manuals/Tricks.html

bugs

library(nlme)
data(Muscle)
muscleRagged = winBugsRaggedArray(Muscle, effects="Strip",  
observations="conc",
  covariates=list(observations="length"))