[R] normal distribution assumption for multi-level modelling

[Cecile De Cat]

Thanks.   I appreciate this isn't strictly an R question and will
pursue on another list.

The procedure I followed was inspired from
@article{
   Author = {Baayen, R. Harald and Milin, Petar},
   Title = {Analysing Reaction Times},
   Journal = {International Journal of Psychological Research},
   Volume = {3},
   Number = {2},
   Pages = {12--28},
      Year = {2010} }

Best,

Cecile


On 18 April 2012 19:55, Bert Gunter <gunter.berton at gene.com> wrote:
>
> Cecile:
>
> On Wed, Apr 18, 2012 at 8:21 AM, Cecile De Cat <c.decat at leeds.ac.uk> wrote:
> > Hello,
> >
> > I'm analysing reaction time data from a linguistic experiment (a variant of
> > a lexical decision task).   To ascertain that the data was normally
> > distributed, I used *shapiro.test *for each participant (see commands
> > below), but only one out of 21 returns a p value above p.0 05.
> >
> >> f = function(dfr) return(shapiro.test(dfr$Target.RTinv)$p.value)
> >> p = as.vector(by(newdat, newdat$Subject, f))
> >> names(p) = levels(newdat$Subject)
> >> names(p[p < 0.05])
> >
> > Removing a few outliers
>
> !! Yikes!! I won't say "Don't do this." But I will say that this can
> be a very dangerous and unscientific thing to do, leading to biased,
> misleading results.
>
>  per subject doesn't make a difference, and
> > "aggressive" removal of outliers (done by subject, for each of the 6
> > conditions ) still results in non-normally distributed data by subject.
> >
> > Does this invalidate any attempt at multi-level modelling?
>
> How can we possibly know without knowing in detail the objectives of
> the investigation, the nature of the data, and the details of the
> analysis you did??!
>
> On general principles, normality is rarely of any real importance;
> lack of independence (or, in general, non-adherence to the covariance
> structures specified) usually is.  So "any attempt" seems too general
> a claim to support. Indeed, a good graphical analysis -- often the
> most scientifically informative thing to do anyway -- is almost always
> a good thing to do.
>
> As this has little to do with R, you should follow up on a statistical
> list, like stats.stackexchange.com .
>
> -- Bert
> >
> > Many thanks in advance for your help.
> >
> > Cecile
> >
> >        [[alternative HTML version deleted]]
> >
> > ______________________________________________
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> > https://stat.ethz.ch/mailman/listinfo/r-help
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> > and provide commented, minimal, self-contained, reproducible code.
>
>
>
> --
>
> Bert Gunter
> Genentech Nonclinical Biostatistics
>
> Internal Contact Info:
> Phone: 467-7374
> Website:
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