[R-sig-ME] Distributional assumptions + case studies (was: Random or Fixed effects appropriate?)

Andrew Robinson A.Robinson at ms.unimelb.edu.au
Thu Apr 10 22:28:00 CEST 2008


Hi Reinhold,

thanks very much!  

Your paper is eminently suitable, especially insofar as it captures
the interplay between model choice and statistical outcome.  I do
suggest that you make whatever alterations you deem suitable to
preclude any problems with your future publisher, and if possible,
provide some informal commentary on the structure of the analysis - eg
how do you interpret the graphics that you produced, what motivated
your decisions, etc.  Your abstract already includes a description of
the characteristics that makes sthis study interesting as a case
study, so that's very convenient.

In general, my plan is to focus on case studies for which the data are
unencumbered and the authors don't mind providing a detailed
explanation of their analyses.  The sort of thing that I'm envisioning
is along the lines of a cleaned up version of the analysis from p 116
to 137 of this document:

http://www.ms.unimelb.edu.au/~andrewpr/r-users/icebreakeR.pdf

So, much more detail about the process of the analysis than would be
in a published paper (hopefully therefore side-stepping any copyright
issues), but much less detail about the context.  

However, these ideas are not set in stone.  I suppose that much of
data analysis is a question of style, so we can't afford to be
dogmatic.  In the unlikely event that we get an overwhelming response
then we might invoke some kind of filter.  

Ideally a submission would be a Sweave file and a data file, so the
analysis gets dsiscussed in the context of the code that is being run.
I'm happy to provide advice and/or templates for using Sweave, which I
have found invaluable.

Warm regards,

Andrew


On Thu, Apr 10, 2008 at 05:51:36PM +0200, Reinhold Kliegl wrote:
> Hi Andrew,
> 
> The manuscript  (Kliegl, R., Masson, M.E.J., & Richter, E.M. (2007).
> Fixed and random effects of word frequency and masked repetition
> priming: A linear mixed-effects model perspective) is available as PDF
> at the top of my publications page here:
> 
> http://www.psych.uni-potsdam.de/people/kliegl/personal/pubs-e.html
> 
> I will send you a LaTeX version later this week. What all do you need?
> For case studies, it may make sense to include data and R-scripts. Is
> this your plan?
> 
> My co-authors and I realize that the manuscript is in need of an
> overhaul with respect to the precision of some of the arguments
> (especially with respect to justifications of data
> transformation--another red herring in experimental psychology, aside
> from p-values); we already have a very helpful set of reviews from a
> first submission. Not sure yet, where we will go next with it.
> Suggestions?
> 
> Thanks and all the best,
> Reinhold
> 
> On Thu, Apr 10, 2008 at 12:06 AM, Andrew Robinson
> <A.Robinson at ms.unimelb.edu.au> wrote:
> 
> >  >
> >  > In analyses of reaction times (using subjects and items as crossed
> >  > random factors; carried out with Mike Masson and Eike Richter, 2007),
> >  > model-based estimates of correlations among random effects revealed
> >  > "clearer" patterns than the correlations between means and effects
> >  > computed for each subject (as they should, given that they were
> >  > corrected for unreliability). Unlike for fixed-effects estimates,
> >  > however, estimates of correlations among random effects were quite
> >  > susceptible to violations of distributional assumptions for the
> >  > residuals--up to a change in the sign of the correlation!
> >
> >  This is a very interesting observation, and one that I suspect should
> >  not be buried in an email.  Can you tell us more about it?  In my
> >  workshops, I spend a lot of time focusing on the use of diagnostics to
> >  check distributional assumptions.  It would be fabulous to be able to
> >  identify a case study in which getting the distributional assumptions
> >  was so clearly important.
> >
> >  More generally, I wonder if it might be worth collecting such a set of
> >  case studies with clear and thorough analyses and wrapping them in a
> >  document.  It seems to me that it would answer the request made by
> >  Iasonas Lamprianou recently.
> >
> >  I'd be happy to coordinate such an effort, so long as the
> >  contributions were in LaTeX and Sweave.  I know my students would
> >  benefit from it :)
> >
> >  Is there any interest in such an idea, from potential conributors or
> >  (equally importantly) potential users?
> >
> >  Cheers
> >
> >  Andrew
> >
> >

-- 
Andrew Robinson  
Department of Mathematics and Statistics            Tel: +61-3-8344-6410
University of Melbourne, VIC 3010 Australia         Fax: +61-3-8344-4599
http://www.ms.unimelb.edu.au/~andrewpr
http://blogs.mbs.edu/fishing-in-the-bay/




More information about the R-sig-mixed-models mailing list