How to add weights parameter to Generalized Mixed Model

Specific Domains Statistics
21

Just copying and pasting @dmbates code in the first answer, I’m also getting a different result in variance, Std.Dev and Std.errors estimates.

using RDatasets, MixedModels

titanic = RDatasets.dataset("datasets", "Titanic");

m = fit(GeneralizedLinearMixedModel, @formula(Survived ~ 1 + Age + Sex + (1|Class)), titanic, Binomial(), wts=float.(titanic.Freq))

m
Generalized Linear Mixed Model fit by maximum likelihood (nAGQ = 1)
  Survived ~ 1 + Age + Sex + (1 | Class)
  Distribution: Binomial{Float64}
  Link: LogitLink()

  Deviance: 2227.9565

Variance components:
         Column    Variance  Std.Dev. 
Class (Intercept)  26.841378 5.1808665

 Number of obs: 32; levels of grouping factors: 4

Fixed-effects parameters:
────────────────────────────────────────────────────
             Estimate  Std.Error    z value  P(>|z|)
────────────────────────────────────────────────────
(Intercept)   1.12409    2.76454   0.406611   0.6843
Age: Child    1.04558    2.03346   0.514188   0.6071
Sex: Male    -2.41575    1.16525  -2.07317    0.0382
────────────────────────────────────────────────────

I’m on MixedModels v2.3.0