[R-sig-ME] Incorrect output from nested model with mapped pars

[Ben Bolker]

   PPS  We appreciate your adding the RDS for reproducibility, but ... 
most binary attachments are stripped by the mailing list.  It would be 
best if you posted this to the glmmTMB issues list, where you can attach 
files (maybe not .rds though ...)

On 6/30/20 9:22 PM, Christopher Nottingham wrote:
> One more question. Why is the summary function giving the z value and associated p-value. A gaussian error structure is assumed, so shouldn't t values be used to obtain p values.
>
> Thanks,
> Chris
>
> From: Christopher Nottingham
> Sent: Tuesday, 30 June 2020 5:06 PM
> To: 'r-sig-mixed-models using r-project.org' <r-sig-mixed-models using r-project.org>
> Subject: Incorrect output from nested model with mapped pars
>
> I have a dataset with a variable labelled n_comm that is not relevant to some factor level combinations. I am fitting a nested model to this data and fixing betas representing the irrelevant factor combinations to 0 using map. As shown following, the model output from the summary table does not match what should be produced.
>
>> map_names = list(beta = factor(c(1:6, NA, 8)))
>> fit = glmmTMB(log(Err) ~ model + n_surv + species + n_comm:geostatistical + intensity,
> +               data = Bhat_all.df,
> +               start = list(beta = ifelse(is.na(map_names$beta), 0, 1)),
> +               map = map_names)
>> summary(fit)
> Family: gaussian  ( identity )
> Formula:          log(Err) ~ model + n_surv + species + n_comm:geostatistical +      intensity
> Data: Bhat_all.df
>
>       AIC      BIC   logLik deviance df.resid
>   18340.8  18394.7  -9162.4  18324.8     6212
>
>
> Dispersion estimate for gaussian family (sigma^2): 1.11
>
> Conditional model:
>                                      Estimate Std. Error z value Pr(>|z|)
> (Intercept)                        9.329e+00  5.461e-02  170.82   <2e-16 ***
> modelbiomass-dynamics             -4.082e+00  5.089e-02  -80.22   <2e-16 ***
> modelsize-structured              -4.092e+00  5.056e-02  -80.93   <2e-16 ***
> n_surv                            -8.895e-04  8.146e-05  -10.92   <2e-16 ***
> species$\\mathit{S. aequilatera}$  5.596e-01  2.677e-02   20.90   <2e-16 ***
> intensityFishing intensity: high   3.589e-01  2.681e-02   13.39   <2e-16 ***
> n_comm:geostatisticalFALSE         0.000e+00  7.450e-05    0.00    1.000
> n_comm:geostatisticalTRUE         -3.245e-04  5.461e-02   -0.01    0.995
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> Warning message:
> In cbind(Estimate = coefs, `Std. Error` = sqrt(diag(vcov))) :
>    number of rows of result is not a multiple of vector length (arg 2)
>> rbind(sqrt(diag(solve(fit$obj$he()))))
>             [,1]       [,2]       [,3]         [,4]       [,5]       [,6]         [,7]       [,8]
> [1,] 0.05458617 0.05086506 0.05053495 8.142355e-05 0.02675588 0.02679859 7.446289e-05 0.01792267
>> fit$sdr
> sdreport(.) result
>             Estimate   Std. Error
> beta   9.3291879616 5.461347e-02
> beta  -4.0822725635 5.089050e-02
> beta  -4.0920631052 5.056022e-02
> beta  -0.0008895195 8.146427e-05
> beta   0.5595933469 2.676926e-02
> beta   0.3589326271 2.681199e-02
> beta  -0.0003244617 7.450013e-05
> betad  0.1082286532 1.793163e-02
> Maximum gradient component: 0.001913387
>
> The output below is wrong (there should be no std err, on a mapped value and the other values are incorrect.),
> n_comm:geostatisticalTRUE         -3.245e-04  5.461e-02   -0.01    0.995
>
> The dataset is attached as a rds for reproducibility.
>
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>
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