[R-sig-ME] Reporting main effects in glmer
Francesco
fbromano at sabanciuniv.edu
Wed Jan 29 12:22:59 CET 2014
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)
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: .....
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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