[R] How to do covariate adjustment in R

[Timothy Bates]

Dear Karena,

x = 1:100
y = rnorm(100)

fit = lm(x~y)
# what properties does a fit have?
names(fit)
 # [1] "coefficients"  "residuals"     "effects"       "rank"          "fitted.values" "assign"        "qr"           
 # [8] "df.residual"   "xlevels"       "call"          "terms"         "model"        

x.resid = fit$residuals
plot(x~x.resid)
cor.test(y,x.resid) # -> r = 3.019388e-17 


A gotcha is NAs in your data frame: Look at ?lm to see how to handle these properly
best, t

On 20 May 2011, at 6:58 AM, karena wrote:

> Thank you so much for this reply, Peter. It helps.
> 
> I know this is one way to adjust for covariates. However, if what I want is
> to get the 'remaining values' after adjustment. For example, say, 'gene
> expression' value is denoted as 'ge', and for each gene, 
> ge=a*age+b*sex+c*per_se
> 
> My question is: how to get the value of 'per_se' for each gene?
> 
> thanks again.
> 
> Karena
> 
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