[BioC] nested model: lme, aov and LSMeans

James W. MacDonald jmacdon at med.umich.edu
Tue Feb 13 17:26:40 CET 2007

Hi Shirley,

shirley zhang wrote:
> Dear all,
> I posted my question a few days ago, but haven't receive any response
> yet. Could anybody help me? Appreciate any hints and suggestions.

You likely didn't get a response because you aren't really doing 
anything pertinent to Bioconductor (except possibly you are using 
microarrays, although you don't say).

Anyway, both aov() and lme() are either part of base R, or a recommended 
package, so your question probably belongs on the R-help list.

A word to the wise - LSMeans are an invention by the SAS people that 
tend to raise passions almost as much as type III sums of squares on 
R-help. You are probably better off using RSiteSearch("LSMeans") to find 
out what you want to know rather than asking directly.



> ==============================
> I'm working with a nested model (mixed).
> I have four factors: Patients, Tissue, sex, and tissue_stage.
> Totally I have 10 patients, for each patient, there are 2 tissues
> (Cancer vs. Normal).
> I think Tissue and sex are fixed. Patient is nested in sex,Tissue is
> nested in patient,  and tissue_stage is nested in Tissue.
> I tried aov and lme as the following,
>>aov(gene ~ tissue + gender + patients%in%gender + stage%in%tissue
>>lme(gene ~ tissue + gender, random = list(patients = ~1 , stage = ~ 1))
> I got results from aov, but I got error message from lme which is
> false convergence (8). so I could not compare the results of aov with
> lme.
> Could anybody tell me whether I use the correct command? How can I get
> LSMeans for Cancer vs. Normal in R ( I know it is easy in SAS)?
> Thanks,
> Shirley
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James W. MacDonald, M.S.
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109

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