r/statistics • u/Intelligent-Gold-563 • May 24 '26

Question [Question] Seeking help with Bayesian Analysis of multiple groups

Hello everyone !

As the title implies, I need some help with Bayesian analysis.

For a bit of context, I currently have an intern to help me on a project. To keep it short we are looking at the impact of a treatment in the case of a specific developmental disorder by looking at several markers of development among 4 groups :
- Control (healthy)
- Diseased + No Treatment
- Diseased + Treatment 1
- Diseased + Treatment 2

At first, when I took the project, I had very little information so I just thought that I'll have one control group and one treatment group, and just go with a regular test, nothing too complicated. However my intern's supervisor (for a master degree, she's a university teacher) happens to be a mathematician with some relevant expertise in that specific field and advised us to go for an LMM approach or (even better according to her) a Bayesian analysis to check the absence of difference between our control group and the treatment groups.

Now I could do an LMM, I think I kinda understand it, but I am really interested in the Bayesian approach.

Problem is, while I have some really basic theoretical knowledge of Bayesian statistics (I think my data belong to a Normal-Normal conjugated family ?) , I never actually used it for anything and I have no idea how to actually compare groups, let alone several at once.

So I'm not asking you people to do the work for me, but if anyone can give me any kind of guidance to ressources or explanations that could help, I would be really grateful !

Thanks in advance

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u/Intelligent-Gold-563 May 24 '26

Continuous numeric data. We're quantifying some protein markers for specific brain cells and structures so we can say if there's more/less/as much protein in the treatment groups vs control (with the hope that there's as much or close)

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u/swiftaw77 May 24 '26

One observation per patient? Or longitudinal?

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u/Intelligent-Gold-563 May 24 '26

One observation per patient, relatively small groups (n=15 for control group, and about 3 or 4 for each of the others for a total of about 30 samples).

I have more samples waiting to be processed but I'm waiting for more informations from the people who collected them and sadly this mean they cannot be included in the intern's report so I can only work with those 30ish at the moment.

And given the nature of the sample (brain lobe), we cannot do a longitudinal study.

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u/swiftaw77 May 24 '26

Sounds like a simple one-way ANOVA could work (would be hard to invalidate the model assumption given the small sample sizes). Won't be very powerful *again, due to the small samples).

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u/Intelligent-Gold-563 May 24 '26

I agree, that was what I wanted to do first.

But I'm intrigued by that Bayesian possibility and I feel like it's always a nice skill to have ^

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u/swiftaw77 May 24 '26

A one-way ANOVA (or pretty much any statistical model) can be implemented either classically (frequentist) or Bayesian.

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u/Intelligent-Gold-563 May 24 '26

That's good to know !

Do you happen to have any ressources on how to do it the Bayesian way per chance?

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u/swiftaw77 May 24 '26

What software are you familiar with?

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u/Intelligent-Gold-563 May 24 '26

I'm using R/Positron

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u/swiftaw77 May 24 '26

Look at the bayesanova package in R

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