On Wed, Jan 29, 2014 at 5:22 AM, Francesco <fbromano@sabanciuniv.edu> wrote:

> Dear all,
>
>
> fairly simple question this time. I need to report a main effect and or
> pairwise comparisons for a model that has a binary DV 'success' and a
> categorical predictor X with three levels (A, B, and C). My model looks
> like this:
>
> Correct ~ 1 + A + (1 | Part) + (1 | Item)
>

I don't understand this.  You write that the categorical predictor is X and
its three levels are A, B and C.   Does the A in the formula refer to an
indicator column derived from X?


>
> The original call was:
>
> >object<-glmer(Correct~1+A+(1|Part)+(1|Item), family=binomial, data=data)
>
>
> with the following summary output:
>
> Generalized linear mixed model fit by maximum likelihood ['glmerMod']
>  Family: binomial ( logit )
> Formula: ......
>    Data: .....
>

It would have been more informative to keep the formula from the output.
The formula given above has only the intercept and A for fixed effects but
your output gives intercept, A and B.  I don't think this output
corresponds to the call given above.


>
>       AIC       BIC    logLik  deviance
>  218.9053  242.0455 -104.4526  208.9053
>
> Random effects:
>  Groups Name        Variance Std.Dev.
>  Part   (Intercept) 9.0129 3.0021
>  Item   (Intercept) 0.7356   0.8577
> Number of obs: 756, groups: Part, 45; Item, 18
>
> Fixed effects:
>               Estimate Std. Error z value Pr(>|z|)
> (Intercept)     -95.14 4122464.75       0        1
> A             89.88 4122464.75       0        1
> B             90.75 4122464.75       0        1
>
> Correlation of Fixed Effects:
>      (Intr)   A
> A -1.000
> B -1.000  1.000
>
> where Part and Item are random effects for participant and items.
> Basically the three groups are very similar in their response, where one
> group (the reference level group in this analysis) has no 0s and all 1s.
> Releveling generates a Pr(>|z|) of .54 for the difference between group B
> and C so I believe the model is ok.
>



>
> In this scenario I would not expect A to have a main effect on the model
> but when I compare it to the same model minus the A predictor, R yields the
> following:
>
>
> > anova(object,objectminusA)
>
> Data: data
> Models:
> objectminusA: Correct ~ 1 + (1 | Part) + (1 | Item)
> object: Correct ~ 1 + A + (1 | Part) + (1 | Item)
>              Df    AIC    BIC  logLik deviance  Chisq Chi Df Pr(>Chisq)
> objectminusA  3 221.64 235.53 -107.82 215.64
> object  5 218.91 242.04 -104.45   208.91 6.7367      2    0.03445 *
>
> My questions are as follows:
> 1. Should this be interpreted as there being a main effect but no
> significant difference exists between the three levels of the predictor?
> 2. How do I report the result in my paper?
>
> Many thanks in advance for any help.
>
>
>
> --
> Frank Romano
>
> Sabanci University
> website: http://sabanciuniv.academia.edu/FrancescoRomano
>
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