[R] simulation

[Bert Gunter]

Suggestions? -- Yes.

1) Wrong list.. Post on R-sig-mixed-models, not here.

2) Follow the posting guide and provide the modelformula, which may
well be the source of the difficulties (overfitting).

-- Bert

On Fri, Dec 16, 2011 at 1:56 PM, Scott Raynaud <scott.raynaud at yahoo.com> wrote:
> I'm using an R program (which I did not write) to simulate multilevel data
> (subjects in locations) used in power calculations. It uses lmer to fit a
> mixed logistic model to the simulated data based on inputs of means,
> variances, slopes and proportions:
>
> (fitmodel <- lmer(modelformula,data,family=binomial(link=logit),nAGQ=1))
>
> where modelformula is set up in another part of the program.  Locations are
> treated as random and the model is random intercept only.  The program is
> set to run 1000 simulations.
>
> I have temperature, five levels of gestational age (GA), birth wieght (BW) and four
> other categorical pedictors, all binary.  I scaled everything so that all my slopes are in the
> range of -5.2 to 1.6 and variances from .01 to .08.  I have a couple of categories
> of GA that have small probabilities (<.10).  I'm using a structured sampling approach
> looking at 20, 60, 100, and 140 locations with a total n=75k.  The first looks like this:
>
>             # groups   n
>             5             800
>             4             2239
>             3             3678
>             3             5117
>             3             6557
>             2             7996
> Total     20           75000
>
> As the level 2 sizes increase, the cell sizes decrease.  When I run this model in
> the simulation I get:
>
> Warning: glm.fit: algorithm did not converge
>
> every time the model is fit (I killed this long before it ran 1000 times).
>
> I tried increasing the number of iterations to no avail.  I suspected linear
> dependencies among the predictors, so I took out GA (same result), put
> GA back and took out BW (same result) and then took out both GA and
> BW.  This ran about half the time with th other half passing warnings
> such as:
>
> Warning: glm.fit: algorithm did not converge
> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
>
> or
>
> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
>
> in addition to some like the original warning.
>
> If I leave everything in but temperature, then it runs fine.  I also tested the full
> model separately at 50 and 75 level 2 units each with total n=75k.  Nothing converged.
>
> I want to include temperature, but I'm not sure what else to try.  Any
> suggestions?
>
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> and provide commented, minimal, self-contained, reproducible code.



-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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Phone: 467-7374
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