R help - Jun 2007 - Can I treat subject as fixed effect in linear model

Hi,

There are 20 subjects grouped by Gender, each subject has 2 tissues
(normal vs. cancer).

In fact, it is a 2-way anova (factors: Gender and tissue) with tissue
nested in subject. I've tried the following:

Model 1: lme(response ~ tissue*Gender, random = ~1|subject)
Model 2: response ~ tissue*Gender + subject
Model 3: response ~ tissue*Gender


It seems like Model 1 is the correct one since my experiment design is
nested design. However, can anybody tell me whether Model2 is
completely illegal?

Thanks

The short answer is that you could fit that fixed-effect model 
using 'lm', for example.  That would make sense if you wanted to make 
inference only about that particular group of 20 subjects AND you 
thought it was inappropriate to consider that their contribution to a 
model would follow a normal distribution. 

      If you want to make inference beyond that group of 20 subjects, 
then the fixed effect analysis is not appropriate.  If you thought it 
was inappropriate to think that individual adjustments for each subject 
were normally distributed, then the question is how far from normal 
might they be. 

      I don't think Model2 is "illegal" in the sense that you are
not
likely to be sent to prison for using it.  However, I wouldn't do it.  
I'd make use your Model 1 and make all the plots that seem consistent 
with that model, as described in Pinheiro and Bates (2000) Mixed-Effects 
Models in S and S-Plus (Springer).  If the plots (or something else) 
suggested that some of my assumptions were inappropriate, then I'd 
consider other alternative models.  However, that could be a lot of 
work, and I wouldn't undertake such an effort without some pretty strong 
justification. 

      Hope this helps. 
      Spencer

shirley zhang wrote:
> Hi,
>
> There are 20 subjects grouped by Gender, each subject has 2 tissues
> (normal vs. cancer).
>
> In fact, it is a 2-way anova (factors: Gender and tissue) with tissue
> nested in subject. I've tried the following:
>
> Model 1: lme(response ~ tissue*Gender, random = ~1|subject)
> Model 2: response ~ tissue*Gender + subject
> Model 3: response ~ tissue*Gender
>
>
> It seems like Model 1 is the correct one since my experiment design is
> nested design. However, can anybody tell me whether Model2 is
> completely illegal?
>
> Thanks
>
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