[R-sig-ME] choice of reference category only changes coefficient with uncorrelated random intercept and slope

[Ben Bolker]

Not sure, but ...

I think this is real. (If I were going to pursue it further I would
probably try running some simulations.)  I think the asymmetry you're
seeing is most likely related to the nonlinearity inherent in a GLMM;
if that's true, then the effect should go away if you were using a LMM
instead of a GLMM ...


On Tue, Sep 5, 2017 at 7:45 PM, David Sidhu <dsidhu at ucalgary.ca> wrote:
>
> Hi Everyone
>
> I have noticed something strange...
>
> I am running a glmer with a single dichotomous predictor (coded 1/0). The model also includes a random subject intercept, as well as a random item intercept and slope.
>
> Changing which level of the predictor serves as the reference category doesn’t change the absolute value of the coefficient, EXCEPT when the random intercept and slope are uncorrelated.
>
> This happens whether I keep the predictor as a numeric variable, or change the predictor into a factor and use the following code:
>
> t1<-glmer(DV~IV+(1|PPT)+(0+dummy(IV, "1")|Item)+(1|Item), data = data, family = "binomial”)
>
> Is this a genuine result? If so, can anyone explain why the uncorrelated random intercept and slope allow it to emerge? If not, how can I run a model that has an uncorrelated random intercept and slope that would prevent the choice of reference category from affecting the result?
>
> Thank you very much!
>
> Dave
>
> ---
> David M. Sidhu, MSc<http://davidmsidhu.com/>
> PhD Candidate
> Department of Psychology
> University of Calgary
>
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