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 -- View this message in context: http://www.nabble.com/How-to-do-adjust-for-sex%2C-age%2C-genotype-for-a-data-tp24534963p24534963.html Sent from the R help mailing list archive at Nabble.com.
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