[R-sig-ME] confint.merMod, bootstrap and weights

Denis Haine denis.haine at gmail.com
Mon Mar 14 15:17:18 CET 2016

That's what I thought, that the weighting was not taken into account.
The weights are used to estimate an underlying causal model. The Poisson
model is used as a Cox regression model with 2-level random effects.
I believe I have to write my own boostrap function, or be happy with the
Wald method for confint.


> The simulation function (sfun()) that's at the core of the parametric
> bootstrap algorithm is ignoring your specified prior weights.  Poisson
> models with weights are somewhat unusual; what are the weights in your
> model supposed to signify?  If you were simulating the data, how would
> you incorporate the weights in the simulation procedure?
>   Ben Bolker

> On 16-03-13 02:30 PM, Denis Haine wrote:
>> Hello,
>> I ran a model as
>> glmer(y ~ x, family = poisson, data, weights = w)
>> and then tried to get confidence intervals with the following:
>> confint(model, method = "boot", parallel = "multicore", ncpus = 4)
>> However I'm getting the following warning message that I'm not receiving
>> when using method "Wald" instead of "boot":
>> Warning message:
>> In sfun(object, nsim = 1, ftd = rep_len(musim, n * nsim), wts = weights)
>>    ignoring prior weights
>> What's the meaning of this message?
>> Thanks for your help,
>> Denis

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