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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