[BioC] unbalanced factorial design

[Naomi Altman]

I find that the simplest thing to do is to write my own function that 
includes the appropriate call to lme.   That way I do not need to worry 
about grabbing components from complicated objects and passing arguments to 
lme.   I do have to write my own calling function for each experiment, but 
that takes only a few minutes.

--Naomi

At 10:15 PM 2/4/2004, Vincent Carey 525-2265 wrote:

> >
> > I am not sure about if bioconductor includes any functions for
> > mixed-effect models. there are several packages in R handles mixed-effect
> > models, the most complete one is nlme.
>
>it is not too difficult to run gene-specific mixed
>effects models using the combination of esApply (in
>Biobase) and lme (in nlme).  the non-trivial part is
>to properly specify the function (esApply parameter FUN)
>to invoke through esApply.  the design will be derivable from
>information in the phenoData component.  all variables
>in phenoData are visible to the FUN for esApply, so the
>model formula can be specified fairly naturally, thanks
>to the environment manipulations provided in esApply
>(by RG).
>
>with appropriately structured experimental designs in
>which expression might vary smoothly but nonlinearly
>as a function of some design variable, nlme models may
>be of interest to fit through esApply as well.
>
>so the question "does bioconductor include functions
>for ... modeling" often has a negative answer -- we don't
>aim to have functions for all conceivable approaches to
>modeling bioinformatic data.  we prefer to have interfaces
>that allow existing functions in R to be reused conveniently
>and at the option of the analyst, in the bioinformatic context.
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111