[R] warning message from nlme

Doran, Harold HDoran at air.org
Mon Jan 9 20:12:54 CET 2006


Yen Lin:

I'd like to try and offer a little help, but I'm still unclear on your
data structure and problem. You say, they are all categorical variables.
But, does this apply also to your dependent variable? If so, lme is the
wrong function to use.

You also say you want to decompose tha variation into wafer, axis,
orientation and data. But then, what is "loc". Do you mean you want to
decompose the variation in data, your DV, into multiple components
including wafer, axis, orientation and loc?

Maybe if you can take some time to clarify your data structure in more
detail and why your lme call is structured as it is it might be easier
to help.

Harold


-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Chia, Yen Lin
Sent: Monday, January 09, 2006 12:42 PM
To: Berton Gunter
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] warning message from nlme

Hi all,

Sorry for the sloppy description of problem.  

I have a dataset called dense.  I want to decompose the
variability/variation into different components such as wafer, axis,
orientation and data.  These variables are all categorical data.  I
converted axis, orientation and location into factors before I ran the
analysis:

lme(Data~1,random=~1|Wafer/axi/ori/loc,data=Dense)

The algorithm returns the standard deviation of each random effect, but
also gives the warning message:

Warning message:
- not meaningful for factors in: Ops.factor(y[revOrder], Fitted)


I wonder what does this warning message mean?  If the factors are not
meaningful, how can I find out which factors the warning message is
referring to?  Thanks.

Yen Lin





-----Original Message-----
From: Berton Gunter [mailto:gunter.berton at gene.com]
Sent: Monday, January 09, 2006 9:34 AM
To: Chia, Yen Lin
Subject: RE: [R] warning message from nlme

> 
> Can someone point out what is the meaning of this warning message? I 
> tried to look at Ops.factor, but I don't understand it since I'm 
> relatively new to R.  Thanks.
> 

No. **Read the posting guide**  and provide sufficient details in your
post so that an answer can be given.

-- Bert

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