Code:

```
# Creation of robust model
design <-model.matrix(~Class+ PC1 + PC2 + PC3)
fit.robust <- lmFit(EL_bc_norm_0, design, method = "robust", maxit=500)
fit.robust.eBayes <- eBayes(fit.robust)
```

I am trying to extract the residuals out of the above model (named design) relating to each gene and subject. But because there isn't a "y" argument in the model.matrix() function, I am unable to use resid(). From what I understand (my background in statistics is weak) `model.matrix()`

is actually finding the parameter estimates, which will later be use by `topTable()`

to find group differences.

One thread says there no reason to examine residuals for microarray data (https://support.bioconductor.org/p/19622/) but nonetheless, I've been asked to do so.

Looking at another guide (http://jtleek.com/genstats/inst/doc/02_11_many-regressions.html) the traditional non-robust fitted model contains "residuals" but they seem to be absent in my fitted model (All I have is df.residual).

I can use "residuals(fit.robust, EL_bc_norm_0)". This appears to work but I am a bit hesitant about what I am doing.

Thank you!