[RsR] Questions about interpreting lmRob output

[Jenifer Larson-Hall]

Thanks so much Kjell. Your response answers most of my questions. Actually, I figured the overlaid plots things out (and the cool fit.models function) by looking through the archives and finding your pdf presentation that showed it (www.stats.ox.ac.uk/~konis/robust/ROBCLA2006-konis.pdf). That was very helpful!

The documentation you sent me privately (Robust.pdf, documentation for S-PLUS library) was helpful in clearing up a few more lingering questions (I guess if others want it they can email you).

Just one more question now:

My sense of robust methods was that they returned values which did not make strict normality and homogeneity of variances assumptions. In the data set I gave in my previous email, there is heteroskedasticity and non-normality distribution of data. So from what I understand from my reading, robust methods will give me a better sense of what's going on in the bulk of my data than least-squares estimates. If this is true, then what is the reason for looking at diagnostic plots? If I find the data is still heteroskedastic and non-normal in the plots after the robust analysis, is this cause for worry?


Dr. Jenifer Larson-Hall
Assistant Professor of Linguistics
University of North Texas
(940)369-8950