Extracting model params/equivalent of broom tidiers in julia?

Hi I am new to Julia and am using it to run mixed models since it’s so much faster. However I’ve no experience with Julia and it feels like online support is scarce. I would like help with extracting model parameters but not sure how to.

In R this is a trivial task with broom tidiers, which gets me everything I want incl random effects, confints, etc. Is there a way to do this in julia?

using MixedModels
using RData

path = joinpath(dirname(pwd()), "liberalism_conjoint\\saved\\df_reduced_julia.rds")
df = load(path)

m1 = fit(MixedModel, @formula(prefer ~ 1 + X1+(1+X1|country)), df)

coeftable, coef, coefnames, stderror, ranef, raneftables, etc. are all mentioned in the docs and have docstrings for online help. There currently isn’t a confint method defined (though that will likely change soon); instead you can compute the shortest coverage interval with shortestcovint on the results of the parametric bootstrap.

In addition to MixedModels itself, there are a number of related packages with their own documentation, e.g. MixedModelsSim, MixedModelsExtras, and MixedModelsMakie. For MixedModelsMakie, you’ll need to load an appropriate Makie backend, e.g. CairoMakie or GLMakie.

There is also JellyMe4 which provides RCall support for MixedModels, enabling you to move models back and forth between Julia’s MixedModels and R’s lme4, which gives you access to the entire R ecosystem.

Finally, @dmbates, @kliegl and I regularly teach a course on MixedModels. The materials are hosted under the RePsychLing organization on GitHub: RePsychLing · GitHub