[R-sig-ME] Testing assumption multilevel analysis

[Katharina Tostmann]

Hello Phillip,

thank you very much for our helpful response!

Now I feel much better to handle with the assumptions in my multilevel
analysis!


Best regards

Katharina

Am Mo., 26. Aug. 2019 um 17:35 Uhr schrieb Phillip Alday <
phillip.alday using mpi.nl>:

> Please keep the list in CC.
>
> As Ben Bolker mentioned in his reply: for most things, the assumptions
> carry over from the non-mixed case and the graphical diagnostics are
> done the same way. I would in general avoid explicit statistical tests
> of model assumptions (e.g. various tests of normality) because, like all
> tests, they have failure modes (especially related to sensitivity and
> specificity) and don't actually tell you what any potential violation of
> assumptions is doing to your statistical procedure.
>
> For multicollinearity, there is one additional diagnostic that lme4
> gives you in its summary output, namely the correlation of fixed
> effects. The exact meaning of this is perhaps a little technical
> (https://stat.ethz.ch/pipermail/r-sig-mixed-models/2009q1/001941.html),
> but in practical terms a high correlation suggests that there may be
> multicollinearity. Multicollinearity also tends to show itself in
> inflated standard errors (in the fixed effects), much as it does for
> standard linear regression.
>
> Regarding independence of errors: I find that to be an assumption that
> is often best checked by knowing something about your data generating
> process. For example, there may be some autocorrelation in the errors
> between observations due to the way data are collected.
>
> Best,
> Phillip
>
> On 26/8/19 2:23 pm, Katharina Tostmann wrote:
> > Hello Phillip,
> >
> > Yes, I know it is a very big question about the assumptions in general.
> > At this time I got a little information about linearity, normal
> > distibution and variance homogenity. But what ist about
> > mulitcollinearity and independency? Do you have any idea to check this
> > in a multilevel context?
> >
> > Thank you in advance.
> >
> >
> > best regards from Germany
> >
> > Katharina
> >
> > Am Mo., 26. Aug. 2019 um 14:14 Uhr schrieb Phillip Alday
> > <phillip.alday using mpi.nl <mailto:phillip.alday using mpi.nl>>:
> >
> >     This is a rather open-ended request -- you're more likely to get
> helpful
> >     advice if you're a bit more specific. For example, which model
> >     assumptions do you want to test in particular? What do your data look
> >     like? Which assumptions do you think your data might violate? Why do
> you
> >     want to explicitly test assumptions? (e.g. Are you worried about
> >     inflated Type-I error? Often it's better to worry less about
> assumptions
> >     per se and instead focus on "does my model capture the relevant
> aspects
> >     of my data?")
> >
> >     Phillip
> >
> >     On 24/8/19 11:08 am, Katharina Tostmann wrote:
> >     > Hello together,
> >     >
> >     > I'm calculating a multi-level analysis in R. However, I do not
> >     understand
> >     > how to test the model assumptions. In my second hypothesis I also
> >     have a
> >     > mediation with, whereby I also have no idea how to test the model
> >     > assumptions.
> >     > Can anyone help here? Thank you and best regards
> >     >
> >     > Katharina
> >     >
> >     >       [[alternative HTML version deleted]]
> >     >
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> >     >
> >
>

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