Question on glmmTMB

   This should be fine. Unlike many mixed model packages, glmmTMB can
handle models with no random effect.  When in doubt, you can just try
out a comparison - this obviously isn't a 100% guarantee that something
works reliably, but in this example all three approaches give very
similar answers:

library(glmmTMB)
library(bbmle)
m1 <- glmmTMB(count~spp + mined, Salamanders, family=nbinom2)
m2 <- MASS::glm.nb(count~spp + mined, Salamanders)
m3 <- mle2(count ~ dnbinom(mu = exp(logmu), size = exp(logk)),
            parameters = list(logmu ~ spp + mined),
            start = list(logmu = 0, logk = 0),
            data = Salamanders)

library(broom)
library(broom.mixed)
tidy(m1)
tidy(m2)
tidy(m3)

On 6/18/21 4:10 AM, Ebhodaghe Faith wrote:

Dear All,

The glmmTMB package is used to model data with mixed effects. For

example:

glmmTMB(count~spp + mined + (1|site), Salamanders, family=nbinom2)

But I'm just curious to know what happens when the package is used to

model

data without random effects (will this still be fine? How does this

compare

with just using the glm function in the MASS package?). See example

below:

glmmTMB(count~spp + mined, Salamanders, family=nbinom2)

With kind regards,
Faith

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