Can I conduct likelihood ratio test with robust linear regression?
I'm using robust linear regression in R (the rlm function). I'm wondering if I can conduct a likelihood-ratio test after running the nested and full model. I wanted to test if c1+c2+c3 combined improves the fit of the model. Can anyone answer from a statistical perspective? mod_nest=rlm(y~x,data=dat,maxit=200) mod_full=rlm(y~x+c1+c2+c3,data=dat,maxit=200) lrtest(mod_nest,mod_full)
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Have you tried running the OLS model on the same data and running the same tests? What type of result do you get? LR test compares two tests in general, why couldn't you compare your RLS models?