How do you add the weight of an observation to a Mixed Model? I thought I could add the Freq column to wt argument, but apparently not. using RDatasets MixedModels titanic = RDatasets.dataset("datasets", "Titanic") titanic.surv_flg = titanic.Survived .== "Yes"; This runs: MixedModels.fit(Generali…

The problem seems to be a difference between the released version of the MixedModels package (v2.3.0) and the master branch on the repository (v3.0.0-DEV). In v2.3.0 the estimated standard deviation of the random effects is over 6 in the model with the interaction term $ julia-1.4.2 --project …

I was looking for something similar to R’s weights glmer(formula = Survived ~ 1 + Age + Sex + (1|Class), family = binomial, weights = Freq, nAGQ = 2, data = as.data.frame(Titanic))

Isn’t that what I wrote? julia> const GLMM = GeneralizedLinearMixedModel; julia> form = @formula(Survived ~ 1 + Age + Sex + (1|Class)); julia> m = fit(GLMM, form, titanic, Bernoulli(), wts=float.(titanic.Freq), nAGQ=3) Generalized Linear Mixed Model fit by maximum likelihood (nAGQ = 3) Survived…

I use nAGQ=3 instead of 2 because you always evaluate the midpoint so you might as well use the next odd number.

I’m not sure. The results seem quite different. R: summary(glmer(formula = Survived ~ 1 + Age * Sex + (1|Class), family = binomial, weights = Freq, nAGQ = 2, data = as.data.frame(Titanic))) [image] Julia MixedModels.fit(GeneralizedLinearMixedModel, @formula(surv_flg ~ 1 + Age + Sex + Age & Sex…

julia> form = @formula(Survived ~ 1 + Age*Sex + (1|Class)); julia> nonzero = filter(:Freq => !iszero, titanic); julia> m = fit(GLMM, form, nonzero, Bernoulli(), wts=nonzero.Freq, nAGQ=3) Generalized Linear Mixed Model fit by maximum likelihood (nAGQ = 3) Survived ~ 1 + Age + Sex + Age & Sex + (1…

#facepalm Thanks for your help/patience. The /beta coefficients line up now. Followup: Any idea why the std.error, z-value, and p-values don’t match? as.data.frame(Titanic) %>% mutate(Age = relevel(x = Age, ref = "Adult"), Sex = relevel(x = Sex, ref = "Female")) %>% glmer(for…

The standard errors, z-values and p-values match more-or-less with the results I posted. Keep in mind that these are even more approximate for a GLMM than for a LMM so “matching results” should be done with a rather wide tolerance.

@dmbates I must be really dense today or something is off in my install (Win10-64). Using Julia 1.4.2 [image] I updated MixedModels [image] and ran your initial example code: [image] which for me yields [image] and not your results [image] I’ve gotten the same results with both the Julia…

I was using MixedModels#master as in (@v1.4) pkg> add MixedModels#master It seems that the coefficients are properly estimated but the standard deviation of the random effects and the standard errors are incorrect. @palday Do you recall if there was an issue related to weights in the released ver…

How to add weights parameter to Generalized Mixed Model

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dmbates June 24, 2020, 4:43pm 11

To get the same answers as the call to glmer you would need to change the order of the levels on Age and Sex.

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How to add weights parameter to Generalized Mixed Model

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