[R] How to do adjust for sex, age, genotype for a data

[1Rnwb]

then what will be the other factors needed to be adjusted and whether I
should adjust or use them as covariates. Finally how these analysis will be
done in R


Harrell, Frank E wrote:
> 
> 1Rnwb wrote:
>> Hello R gurus,
>> 
>> I am biologist doing biomarker research and I have a data set where I
>> have 6
>> proteins and close to 3000 samples, i have to look for differences
>> between
>> disease(Y) and controls(N) along with genetic risk, genotypes, sex and
>> other
>> demographic info available. however i do not know any of the statistics
>> to
>> do the adjustment for sex, age, genotype, genetic risk. I have been
>> reading
>> in papers where the authors are talking about adjusting for age, sex,
>> genotype, genetic risk. The CDC website suggests for adjusting the age
>> using
>> the weights, but I am not sure as this would apply to my data. one
>> website
>> says that if the distribution is not equal then one has to model sex, age
>> and other demographic parameters as co-variates. I would appreciate if
>> someone can help me to understand this more clearly and provide
>> directions
>> on modeling these to do my analysis. I am attaching a sample data file
>> with
>> this post. Thanks
>> http://www.nabble.com/file/p24534963/Sample%2Bdata.csv Sample+data.csv 
> 
> If the only clinical variables you are adjusting for are age and sex 
> this analysis will be misleading at best.
> 
> Frank
> 
> -- 
> Frank E Harrell Jr   Professor and Chair           School of Medicine
>                       Department of Biostatistics   Vanderbilt University
> 
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> 

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