Dear R-List, 

due to outliers in my data I wanted to carry out a robust regression. 
According to APA standards, reporting OLS regression results should include
 
1. unstandardized beta coefficients
2. standardized beta coefficients
3. SE
4. t values
5. r squared
6. r squared adjusted
7. F (df.num/df.den)

Now I tried the robust version using lmrob (package="robustbase")

lmrob.fit<-lmrob(y~x1+x2+x3,data=mydat)

I got 
1. unstandardized beta coef
3. SE
4. t values

What about? 
2. standardized beta coef
5. r squared
6. r squared adjusted
7. F (df.num/df.den)

I have read in an R-threat (http://tolstoy.newcastle.edu.au/R/e5/help/08/11/7271.html) that R2 is only valid in the context of least-square methods. Is there no equivalent I could report for non-least-square methods? Then why does lmrob-output not include standardized beta coefs and F statistic? How can I compute both of them?

Then I realized that ltsReg (package="robustbase") does actually report almost everything I would need, but I could not find "standardized beta coefficients" (does anyone know how I could compute these coefs?)
Though, the authors of the package "strongly recommend using lmrob() instead of ltsReg". Is this due to inefficiency or are the coefs biased? 

Finally I found lmRob (package="robust") which does report at least a multiple R2, but which is apparently biased and needs correction as I found in a threat of Renaud & Victoria-Feser  https://stat.ethz.ch/pipermail/r-sig-robust/2010/000290.html

where the authors recommend to correct R2 for bias (Renaud, O. & Victoria-Feser, M.-P. (2010). A robust coefficient of determination for regression. Journal of Statistical Planning and Inference, 140, 1852-1862. http://dx.doi.org/10.1016/j.jspi.2010.01.008). Does that mean, that "multiple r squared" can be reported even though it is not a least square method, but should be corrected for bias? Then, what does that mean for the rest of lmRob-output (e.g. t-values)? 

I must confess that I am somewhat confused and I would be very thankful for any clarification in this matter. 
Thank you in advance and sorry for my question if it reveals some serious lack of knowledge on my side.

Best wishes.

Alain

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