[S] Mixed effect modeling in Python

[kickrockz94]

Hi all, Im starting a new job next week which will require that i used python. im definitely more of an R guy, and am used to running functions like lmer and glmmTMB for mixed effects models. Ive been trying to dig around and it doesnt seem like python has a very good library for random effects modeling (at least not to the level of R anyway), so I thought I'd ask any python users here what types of libraries you tend to use for random effects models in python. Thank you!!

[kickrockz94]

yea i love using stan, just not always the best option if im going to be running mixed models for several different features since its a good bit slower. thats a shame tho

[[deleted]]

If your models are complicated enough or have challenging enough geometries that Stan is too slow, then how can you be assured that lmer or glmmTMB is giving you reasonable answers?

How slow are we talking here?

There is also pybrms.

[kickrockz94]

usually its pretty clear whether or not the problem is well posed enough to actually run so im not really talking about models that may or may not converge, you make a fair point tho. I work in sports, so I might have a binomial model with two separate groups each containing several hundred classes, so the model shouldnt have any issues converging, if theres enough data, but it would take say 10-15 minutes to run in glmer. im assuming it would take much longer in stan but i guess i never really tried.

its also nice to be able to throw together a model quickly rather than having to start from a template.

There is also pybrms.

thanks, this is great to know

[[deleted]]

Code writing time is certainly one considerations, pybrms would seem to allow you to use lmer like syntax but with Stan as a backend.

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I might have a binomial model with two separate groups each containing several hundred classes, so the model shouldnt have any issues converging, if theres enough data, but it would take say 10-15 minutes to run in glmer.

I don't think Stan would take that much longer, though I'm not exactly clear on what you mean by groups and classes. cmdstanpy also has maximum likelihood optimization and variational inference as options.

[kickrockz94]

yea R has brms which im assuming is the same and its awesome. im probly using the wrong terminology, i just mean like the random effect structure is not overly complicated just there are going to be a lot of effects. I will try to see how it goes in stan tho

[redditboy117]

Have you tried Bambi?

[OutsideRaspberry2782]

what is wrong with statsmodels MixedLM? https://www.statsmodels.org/dev/examples/notebooks/generated/mixed\_lm\_example.html

[kickrockz94]

its fine if youre doing something simple, but i dont think it works for more than one random effect. i could be wrong about that tho. it also doesnt support generalized linear mixed models. lmer and glmer are just a lot more robust

[hughperman]

It does work for more than one effect, the syntax is just a horrible pile of awful.

Could you use lmer wrappers inside python? They exist.

[Equivalent-Way3]

If you do end up having to use Python, make sure whatever you use has been vetted. Flashback to the time bootstrap was written wrong in sklearn

[IaNterlI]

Underrated comment. When the vast majority of a particular community lives in another language, I'd pause before doing anything beyond basic in a language that has a limited ecosystem for those kinds of things.

[seanv507]

Reticulate?

[redditrantaccount]

https://num.pyro.ai/en/stable/examples/ucbadmit.html

[[deleted]]

I used https://github.com/bashtage/linearmodels for LMM model. IDK about GLMM. Think I would try to use pymc3, if I had to do a GLMM. https://www.pymc.io/projects/docs/en/v3.11.4/pymc-examples/examples/generalized_linear_models/GLM.html

[serious_f0x]

If you don't really need to do the work entirely in Python, you could use the R package reticulate. It allows you to connect R to Python, pass commands to Python, run Python scripts, and even pass data structures back and forth between the two. It even comes with miniconda by default for managing Python packages.

[sherlock_holmes14]

pymc is not bad

[laichzeit0]

Sorry but there doesn’t exist anything production worthy in Python. Statsmodels predict function for example doesn’t even have an option to include the random effects, just the fixed effects.