[R] How to deal with this random variable?

Manuel Ramon manugen at gmail.com
Tue Jul 28 10:47:55 CEST 2009


Thank you for your replay Bert. You are right, is complicated to get a good
response when people do not know how the experiment was conducted, etc. The
main problem, maybe, is that this experiment has a wrong design being
complicated to get some good conclusion from it. I read this forum
frequently and I found a lot of useful information on it. For that reason I
decided to ask to the forum; maybe someone can help us.
Thank you again for your response Bert.



Bert Gunter wrote:
> 
> This sounds way too complicated for this forum, which is designed to
> provide
> help to users on the  use of the R language, not remote statistical
> consulting. While you may receive replies, I would argue that you would do
> better to find a local statistical expert with whom to work -- not least
> because they should probably have a deep understanding of how your
> experiment was conducted, data gathered, measurements made, etc. to be
> able
> to give you worthwhile advice.
> 
> Long distance consulting based on incomplete understanding is very risky.
> Caveat emptor!
> 
> Bert Gunter
> Genentech Nonclinical Biostatistics
> 
> 
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
> On
> Behalf Of Manuel Ramon
> Sent: Monday, July 27, 2009 9:54 AM
> To: r-help at r-project.org
> Subject: [R] How to deal with this random variable?
> 
> 
> Hello to everybody,
> I have a data frame with 100 measures of quality for 3 variables: A, B and
> C. These quality variables are measured in diferent times along the
> productive process. My data comes from 5 experiments (5 replicates with 20
> measures for replicate). I also have a final measure (Z) but just one
> measure for each unit, that is, for the 20 units that are measured on each
> replica. 
> 
> My objetive is to study the relationships between the 3 quality parameters
> with the last measure, that is:
>  
>   lm(Z ~ A+B+C, data=mydata)
> 
> I have found significant differences between replicas for each qualite
> parameters (A, B and C) and I would like to include the replica effect as
> a
> random effect:
> 
>   lme(Z ~ A+B+C, data=mydata, random=~1|replica)
> 
> And here is my problem. I know that there are signifficant diferences
> between replicas but since the final measure, Z, is the same for each
> replica I do not know how to deal with. 
> 
> Can you help me? How could I take into account the variability due to the
> replica when I want to study the effects of variables A, B and C on the
> final result of a productive process?
> 
> Thank you in advance.
> 
> -----
> Manuel Ramón Fernández
> Group of Reproductive Biology (GBR)
> University of Castilla-La Mancha (Spain)
> mramon at jccm.es
> -- 
> View this message in context:
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> 4341.html
> Sent from the R help mailing list archive at Nabble.com.
> 
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> ______________________________________________
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> PLEASE do read the posting guide
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> 
> 


-----
Manuel Ramón Fernández
Group of Reproductive Biology (GBR)
University of Castilla-La Mancha (Spain)
mramon at jccm.es
-- 
View this message in context: http://www.nabble.com/How-to-deal-with-this-random-variable--tp24684341p24695050.html
Sent from the R help mailing list archive at Nabble.com.




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