[R-sig-ME] Testing assumption multilevel analysis
to@tm@nnk@th@r|n@ @end|ng |rom gm@||@com
Tue Aug 27 09:26:01 CEST 2019
thank you very much for our helpful response!
Now I feel much better to handle with the assumptions in my multilevel
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
> 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.
> 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
> > 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
> > want to explicitly test assumptions? (e.g. Are you worried about
> > inflated Type-I error? Often it's better to worry less about
> > per se and instead focus on "does my model capture the relevant
> > 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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