[R-sig-ME] Function to create candidate model list

[Raymond Danner]

Thanks Andy,

I'll look into it!

Ray


On 7/14/10 12:00 PM, "Andy Fugard" <andyfugard at gmail.com> wrote:

> There's one here:
> 
>     http://www.andyfugard.info/TypeII_Lmer.R
> 
> which might give you some clues for how to write what you really want.
>  (See examples at end.)  It does a sort of iterated "drop1" - only on
> the fixed effects.  It doesn't touch the random effects at all, which
> means you'll end up with nonsense if you have a random slope, e.g.,
> models of these forms will be compared.
> 
>    ?y ~ 1 + x + (x|id)
> ?   y ~ 1 ? ? + (x|id)
> 
> Here's example output:
> 
> lmer.typeII(r2 ~ (Anger * Gender * btype * situ) + (1|id) + (1|item),
>  family = binomial, data = VerbAgg)
> 
>                             AIC    BIC Chisq Chi Df Pr(>Chisq)
>  Anger                    -9.52  -2.58 11.52      1       0.00
>  Gender                   -0.78   6.15  2.78      1       0.10
>  btype                   -27.88 -14.01 31.88      2       0.00
>  situ                    -15.20  -8.27 17.20      1       0.00
>  Anger:Gender              2.00   8.93  0.00      1       0.98
>  Anger:btype               2.03  15.90  1.97      2       0.37
>  Anger:situ               -0.63   6.30  2.63      1       0.10
>  Gender:btype            -14.83  -0.96 18.83      2       0.00
>  Gender:situ               1.48   8.42  0.52      1       0.47
>  btype:situ                2.75  16.61  1.25      2       0.53
>  Anger:Gender:btype        0.87  14.74  3.13      2       0.21
>  Anger:Gender:situ        -0.09   6.85  2.09      1       0.15
>  Anger:btype:situ          3.32  17.19  0.68      2       0.71
>  Gender:btype:situ         3.33  17.20  0.67      2       0.71
>  Anger:Gender:btype:situ   3.57  17.44  0.43      2       0.81
> 
> For instance the row for Anger is the result of comparing these two models:
> 
>  r2 ~ Anger + Gender + btype + situ + (1 | id) + (1 | item)
>  r2 ~         Gender + btype + situ + (1 | id) + (1 | item)
> 
> (the AIC and BIC columns are differences; Chisq is the log-likelihood
> ratio.)
> 
> The row for Anger:Gender is the result of comparing:
> 
>  r2 ~ Anger + Gender + btype + situ + (1 | id) + (1 | item) +
>      Anger:Gender + Anger:btype + Anger:situ + Gender:btype +
>      Gender:situ + btype:situ
>  r2 ~ Anger + Gender + btype + situ + (1 | id) + (1 | item) +
>                   + Anger:btype + Anger:situ + Gender:btype +
>      Gender:situ + btype:situ
> 
> Cheers,
> 
> Andy
> 
> 
> On Wed, Jul 14, 2010 at 17:10, Raymond Danner <rdanner at vt.edu> wrote:
>> 
>> Dear R users,
>> 
>> Could anyone recommend a function that creates a list of all possible
>> candidate mixed models (type lmer) from specified fixed and random
>> variables? ?So that you know where I雋 going--I would then like to rank
>> these models with AIC and calculate model averages with the AICcmodavg
>> package.
>> 
>> Thanks in advance,
>> Ray
>> 
>> ? ? ? ?[[alternative HTML version deleted]]
>> 
>> 
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