glmmTMB: standard error of dispersion parameter

obj <- glmmTMB(deaths~I(NDAM2014^0.14), family=nbinom1(link='log'),

data=DAAG::hurricNamed)

coef(summary(obj))[['cond']][,1:2]

Estimate Std. Error
(Intercept)      1.3003220  0.4764633
I(NDAM2014^0.14) 0.7702897  0.1283899

I would have expected coef(summary(obj))[[?disp?]] to give the information you want,
but it returns NULL.  I judge that this is an oversight. If one specifies a dispformula
that is more than the default ~1, coef(summary(obj))[[?disp?]]  does give the output
that is desired ? see below.  Try however:

obj[['sdr']]

sdreport(.) result
       Estimate Std. Error
beta  1.3003220  0.4764633
beta  0.7702897  0.1283899
betad 4.5529957  0.2116238
Maximum gradient component: 1.733627e-07

betad is the scale parameter, with a log link function.

Observe that exp(4.5529957) = 94.91632, which is what summary(obj) gives as
'Overdispersion parameter for nbinom1 family?.

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Note that if one specifies a dispformula that is more than the default ~1,
coef(summary(obj))[[?disp?]]  does give the required information:

obj2 <- glmmTMB(deaths~I(NDAM2014^0.14), family=nbinom1(link='log'), data=DAAG::hurricNamed,

+ dispformula=~poly(NDAM2014,2))

coef(summary(obj2))[['disp']]

NULL

coef(summary(obj))[['disp']]

Estimate Std. Error   z value     Pr(>|z|)
(Intercept)         3.389720  0.2040211 16.614557 5.467767e-62
poly(NDAM2014, 2)1  7.737363  1.7277783  4.478215 7.526974e-06
poly(NDAM2014, 2)2 -1.780921  1.6305625 -1.092213 2.747396e-01

John Maindonald             email: john.maindonald at anu.edu.au<mailto:john.maindonald at anu.edu.au>

In a fitted glmmTMB object, where do I find the standard error of the
dispersion parameter estimate for a negative binomial model? Thanks!


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