Which error family: beta or bionomial with weights?


I'm investigating the effect of different weather variables (temperature, wind, and rain) on the breeding success of blue tits. My data for breeding success ("overall success") is a proportion bounded between 0 and 1, but also includes 0s and 1s. I was trying to use a glmmabmb with a beta error family, but with no success (model and error message below):

Overall.suc<- glmmadmb(Overall.success~ Av.Temp.Brood+Av.Wind.Brood+Av.Rain.Brood+
family = "beta",link = "logit",
data = b_data)

*Error in glmmadmb(Overall.success ~ Av.Temp.Brood + Av.Wind.Brood + Av.Rain.Brood + : *

  • 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:
    In system(cmd, intern = intern, wait = wait | intern, show.output.on.console = wait, :
  • running command 'C:\WINDOWS\system32\cmd.exe /c glmmadmb -maxfn 500 -maxph 5 -noinit -shess' had status 1*

I then tried switching instead to a glmer with binomial error family and weighting (nest clutch size in this case). This ran but I still got some error messages so I included a glmer control. This also ran but still with some warnings (shown below):

Overall.suc_GLMER<- glmer(Overall.success~ Av.Temp.Brood+Av.Wind.Brood+Av.Rain.Brood
+ (1|NestBoxID),
family= binomial(link= "probit"),
weights = Clutch.size, data = b_data,
glmerControl(optimizer = "bobyqa", optCtrl = list(maxfun = 100000)))
Warning message:
In eval(family$initialize, rho) : non-integer #successes in a binomial glm!

I was wondering if anyone had any alternative/ better suggestions of how to run this model? Ideally without any warning messages...


if you ran it with family gaussian, is it significantly better or worse than the binomial ?

The data for overall success is not normally distributed at all so I didn't think gaussian would work (I've attached the histogram). When I run the model with gaussian I get the warning message shown below:

Overall.suc<- glmmadmb(Overall.success~ Av.Temp.Brood+Av.Wind.Brood+Av.Rain.Brood+

  •                   (1|NestBoxID),
  •                family = "gaussian",link = "identity",
  •                data = b_data)

Warning message:
In eval(substitute(expr), data, enclos = parent.frame()) :
sd.est not defined for this family

overall success

I am not at all familiar with this package, I believe its a non CRAN package ? therefore I don't know how to begin interpreting sd.est complaint.


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