[R-lang] Re: High collinearity in logit linear mixed effects modelling

[T. Florian Jaeger]

well, than you have one null result and one result =). It's not the
strongest case, but at least you can argue that one of your experiments
seems to suggests that it is indeed one of the predictors (rather than the
other) that's driving the effect.

crucially, for the result to be what you probably are looking for, the
factor you're interested in must be the one that if added *second
*still improves
the model significantly.

Florian

On Fri, Jun 25, 2010 at 5:19 PM, Zhenguang Cai <s0782345@sms.ed.ac.uk>wrote:

> yes, I did two cross-language/dialect structural priming studies, with the
> same design and the same materials. In one experiment, Mandarin was the
> response language in one experiment and Cantonese was the response language
> in the other(primes were either in Mandarin and Cantonese in both
> experiments).
>
>
> Zhenguang
>
> T. Florian Jaeger wrote:
>
>> Dear Zhenguang,
>>
>> what do your mean by Experiment 1 and 2? You have two different data sets?
>>
>> Florian
>>
>> On Fri, Jun 25, 2010 at 9:12 AM, Zhenguang Cai <s0782345@sms.ed.ac.uk<mailto:
>> s0782345@sms.ed.ac.uk>> wrote:
>>
>>    Dear Professor Trueswell,
>>
>>    Thanks for the advice. I did that and found that P2 can be subsumed
>>    by P1 but not the other way round. I think that means something.
>>
>>    My further question is that we always at least have to determine 1)
>>    whether P2 can be subsumed by P1 (i.e., whether the addition of P2
>>    can significantly improve model fit) and 2) whether P2 can be
>>    subsumed by P1 (i.e., whether the addition of P2 can significantly
>>    improve model fit). Is that correct?
>>
>>    Zhenguang
>>
>>    John Trueswell wrote:
>>
>>        Zhenguang,
>>
>>        If Experiment 1 and Experiment 2 are similar enough, you could
>>        combine
>>        the data from the two experiments and model the entire set (keeping
>>        Experiment as a predictor in the model, to see if that matters).
>>
>>        John Trueswell
>>
>>
>>
>>        On Thu, Jun 24, 2010 at 5:17 PM, Zhenguang Cai
>>        <s0782345@sms.ed.ac.uk <mailto:s0782345@sms.ed.ac.uk>> wrote:
>>
>>            Dear R-language people,
>>
>>            I realized that this is probably a question that has been
>>            frequently asked
>>            already, so sorry for spam to some people.
>>
>>            I found high correlation between two predictors (P1 and P2)
>>            (r  = .8). So
>>            following Florian's advice, I did model comparisons to try
>>            to exclude one of
>>            the predictors. However, I am not sure whether I did things
>>            in the right
>>            way.
>>
>>            Step 1 (to determine whether P2 can be subsumed by P1)
>>
>>            M0<- lmer(Data~1+(1|Subject)+(1|Item),family='binomial')
>>            M1<- lmer(Data~P1+(1|Subject)+(1|Item),family='binomial')
>>            M2 <- lmer(Data~P1+P2+(1|Subject)+(1|Item),family='binomial')
>>
>>            anova (M0, M1)
>>            anova (M1, M2)
>>
>>
>>            Step 1 (to determine whether P1 can be subsumed by P2)
>>
>>            M0<- lmer(Data~1+(1|Subject)+(1|Item),family='binomial')
>>            M1<- lmer(Data~P2+(1|Subject)+(1|Item),family='binomial')
>>            M2 <- lmer(Data~P2+P1+(1|Subject)+(1|Item),family='binomial')
>>
>>            anova (M0, M1)
>>            anova (M1, M2)
>>
>>
>>            In Experiment 1, I found P2 can be subsumed by P1 but not
>>            the other way
>>            round.
>>
>>            However, in Experiment 2, I found P1 and P2 can be subsumed
>>            by each other.
>>            How to resolve this?
>>
>>
>>            Thanks,
>>
>>            Zhenguang
>>
>>            --
>>            The University of Edinburgh is a charitable body, registered in
>>            Scotland, with registration number SC005336.
>>
>>
>>
>>
>>    --     The University of Edinburgh is a charitable body, registered in
>>    Scotland, with registration number SC005336.
>>
>>
>>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
>
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