[R-sig-ME] Incorrect output from nested model with mapped pars
Ben Bolker
bbo|ker @end|ng |rom gm@||@com
Sun Jul 5 00:31:08 CEST 2020
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.
>
> [[alternative HTML version deleted]]
>
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