[R-sig-ME] glmmADMB question

Sun Jan 8 16:19:52 CET 2017

  A few suggestions:

- your "crazy" parameters below, and your statement that

Some issues with my data are that for one of the conditions, the count
of Ges was 0 for all subjects. Similarly, for some subjects, the count
for Ges  was 0 across all conditions.

 suggest that you have an issue of complete separation (e.g. see
<http://stats.stackexchange.com/questions/128742/mixed-logistic-model-with-complete-separation>;
however, the solutions listed there don't currently work in glmmADMB or
glmmTMB ... are you sure you need zero-inflation?  Lots of zeros doesn't
necessarily mean zero-inflation (it could just mean a Poisson/NB with a
very low mean)

  The options I know of for handling complete separation in GLMMs in R
include the blme package (can do anything glmer does, but *not* NB
models - although you could approximate that via a logNormal-Poisson
model); MCMCglmm; and brms.  The latter two can handle zero-inflated
models, but take you into the deep (Bayesian) end of the pool ...

On 17-01-08 09:32 AM, Jennifer Botting wrote:
> Hi,
> 
> I'm having trouble running a ZIPGLMM in glmmADMB.  I am comparing the
> number of behaviours exhibited by 12 individuals over 7 conditions. Each
> subject was tested 4 times.
> 
>> str(Dat)
> 'data.frame': 329 obs. of  26 variables:
>  $ Subject      : Factor w/ 12 levels "Baraka","Batang",..: 11 11 11 11 11
> 11 11 11 11 11 ...
>  $ Sex          : Factor w/ 2 levels "F","M": 1 1 1 1 1 1 1 1 1 1 ...
>  $ History      : Factor w/ 2 levels "HR","MR": 1 1 1 1 1 1 1 1 1 1 ...
>  $ Session      : int  1 2 3 4 1 2 3 4 1 2 ...
>  $ Order        : int  3 1 1 4 5 5 5 2 1 2 ...
>  $ Condition    : Factor w/ 7 levels "A ","B","BE",..: 1 1 1 1 2 2 2 2 3 3
> ...
>  $ Voc: int  0 0 0 0 7 1 5 5 6 3 ...
>  $ Non  : int  0 0 0 0 0 0 0 0 0 0 ...
>  $ Fac       : int  0 0 0 0 0 0 0 0 0 0 ...
>  $ Ges     : int  0 0 0 0 0 0 0 1 0 0 ...
> ...............................
> 
> The data include a very large number of zeros, so I tried the following
> formula in glmmADMB, starting with Ges as my outcome variable:
> 
> *> m <- glmmadmb(formula = Ges ~ Condition + (1 | Subject), data = Dat,
> family = "poisson", zeroInflation = TRUE) *
> 
> and got the following error:
> 
> Parameters were estimated, but standard errors were not: the most likely
> problem is that the curvature at MLE was zero or negative
> Error in glmmadmb(formula = Ges~ Condition + (1 | Subject), data = Dat,  :
>   The function maximizer failed (couldn't find parameter file)
> Troubleshooting steps include (1) run with 'save.dir' set and inspect
> output files; (2) change run parameters: see '?admbControl';(3) re-run with
> debug=TRUE for more information on failure mode
> In addition: Warning message:
> running command 'C:\windows\system32\cmd.exe /c glmmadmb -maxfn 500 -maxph
> 5 -noinit -shess' had status 1
> 
> When I ran it with debug=TRUE, I got the following output:
> 
> Parameters were estimated, but standard errors were not: the most likely
> problem is that the curvature at MLE was zero or negative
> run failed:  Initial statistics: 7 variables; iteration 0; function
> evaluation 0; phase 1 Function value  3.7639324e+002; maximum gradient
> component mag  1.2938e+001 Var   Value    Gradient   |Var   Value
>  Gradient   |Var   Value    Gradient   1  0.00000  1.2938e+001 |  2
>  0.00000  9.7086e-001 |  3  0.00000  1.6197e+000   4  0.00000 -2.6734e+000
> |  5  0.00000 -5.9309e-002 |  6  0.00000 -2.6798e+000   7  0.00000
> -4.9402e-001 |   - final statistics: 7 variables; iteration 7; function
> evaluation 10 Function value  3.2460e+002; maximum gradient component mag
> -8.0580e-005 Exit code = 1;  converg criter  1.0000e-004 Var   Value
>  Gradient   |Var   Value    Gradient   |Var   Value    Gradient   1
> -7.41263  1.8275e-006 |  2 -0.58080  3.4938e-005 |  3 -0.99038  1.6835e-005
>   4  1.59079  8.0028e-005 |  5  0.06984  3.2566e-005 |  6  1.63706
> -8.0580e-005   7  0.32457  7.7648e-005 |  Initial statistics: 8 variables;
> iteration 0; function evaluation 0; phase 2 Function value  3.2460159e+002;
> maxi... <truncated>
> Error in glmmadmb(formula = Ges ~ Condition + (1 | Subject), data = Dat,  :
>   The function maximizer failed (couldn't find parameter file)
> Troubleshooting steps include (1) run with 'save.dir' set and inspect
> output files; (2) change run parameters: see '?admbControl';(3) re-run with
> debug=TRUE for more information on failure mode
> In addition: Warning message:
> running command 'C:\windows\system32\cmd.exe /c glmmadmb -maxfn 500 -maxph
> 5 -noinit -shess' had status 1
> restored working directory to I:/xxxxx
> removed temp directory
> C:\Users\BO~1\AppData\Local\Temp\1\RtmpiwJxjv\glmmADMB12a03acd7a0c
> 
> 
> I tried adding another fixed effect and the model ran, but gave crazy
> values for the condition levels:
> 
> Call:
> glmmadmb(formula = Ges ~ Condition + History + (1 | Subject),
>     data = Dat, family = "poisson", zeroInflation = TRUE)
> 
> AIC: 257.9
> 
> Coefficients:
>              Estimate Std. Error z value Pr(>|z|)
> (Intercept)    -91.28   91007.00    0.00    0.999
> ConditionB      89.63   91007.00    0.00    0.999
> ConditionBE     88.69   91007.00    0.00    0.999
> ConditionEYC    91.28   91007.00    0.00    0.999
> ConditionF      90.54   91007.00    0.00    0.999
> ConditionFE     91.17   91007.00    0.00    0.999
> ConditionHA     89.59   91007.00    0.00    0.999
> HistoryMR       -2.48       1.02   -2.43    0.015 *
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> 
> Number of observations: total=329, Subject=12
> Random effect variance(s):
> Group=Subject
>             Variance StdDev
> (Intercept)    1.837  1.355
> 
> Zero-inflation: 0.15369  (std. err.:  0.13609 )
> 
> Log-likelihood: -118.968
> Warning message:
> In .local(x, sigma, ...) :
>   'sigma' and 'rdig' arguments are present for compatibility only: ignored
> 
> 
> 
> I tried changing some controls that people had suggested online, such as
> 
>  *admb.opts=admbControl(shess=FALSE,noinit=FALSE)*
> 
> but this didn't work with my model.
> 
> Some issues with my data are that for one of the conditions, the count of
> Ges was 0 for all subjects. Similarly, for some subjects, the count for Ges
> was 0 across all conditions.
> 
> I'd be extremely grateful if you had any advice.
> 
> Jenny
> 
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> 
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