[Rd] Regression stars

Frank Harrell f.harrell at vanderbilt.edu
Sun Feb 10 15:22:49 CET 2013

Great discussion.   Tim's Sinclair quote is priceless and relates to the
non-reproducible research done in some quarters.   Norm's wish to remove
stars altogether is entirely consistent with good statistical practice and
would make a statement that R base adheres to good practice.  I don't think
it will work to add confidence intervals because models can have nonlinear
or interaction terms, and the reference cell for a factor variable may not
be what the analyst chooses for a comparison group.

I would like for us to find a way to, over time, implement Norm's wish to
de-emphasize P-values in general.  The harm done  by P-values is


Norm Matloff wrote
> I appreciate Tim's comments.
> I myself have a "social science" paper coming out soon in which I felt
> forced to use p-values, given their ubiquity.  However, I also told
> readers of the paper that confidence intervals are much more informative
> and I do provide them.  As I said earlier, there is no avoiding that,
> and R needs to report p-values for that reason.  
> Instead, the question is what to do about the stars; I proposed
> eliminating them altogether.  Star-crazed users know how to determine
> them themselves from the p-values, but deleting them from R would send a
> message.
> I did say my proposal was "bold," which really meant I was suggesting
> that R do SOMETHING to send that message, not necessarily star
> elimination.
> One such "something" would be the proposal I made, which would be to add
> confidence intervals to the output.  This too could be just an option,
> but again offering that option would send a message.  Indeed, I would
> suggest that the help page explain that confidence intervals are more
> informative.  (The help page could make a similar statement regarding
> the stars.)
> When I pitch R to people, I say that in addition to the large function
> and library base and the nice graphics capabilities, R is above all
> Statistically Correct--it's written by statisticians who know what they
> are doing, rather than some programmer simply implementing a formula
> from a textbook.  I know that a lot of people feel this is one of R's
> biggest strengths.  Given that, one might argue that R should do what it
> can to help users engage in good statistical practice.  I think this was
> Frank's point.
> Norm
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Frank Harrell
Department of Biostatistics, Vanderbilt University
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