Dear All, My apologies for the naive question. I have proportion data (lesion coverage per area) that is nested within regions and categorized by lesion type I planned to analyze with a beta model. However, given that I have 0s in the data I figured I would need to use zero-inflated beta. I then re…

If you don’t care about the sub-models, and just want to handle the 0s/1s with the Beta distribution, you might like my ordered beta version which you can also estimate with brms: Vignette: GitHub & BitBucket HTML Preview Paper: https://osf.io/preprints/socarxiv/2sx6y/

Do you suspect that your 0’s and 1’s arise from a different data-generating process than the beta-distributed data, or are they in effect rounding errors arising from a beta distribution?

Thanks! Do you know if this will be integrated into brms as a family argument?

Hmmm I’m not sure. The 0s represent cases with no lesions and the 1s represent cases where the whole area is lesioned while the numbers in between represent varying degrees of lesioned area.

This sounds like a fundamentally different data generating process, if indeed there are cases where literally zero area is lesioned and cases where literally all the area is lesioned. If you’d like to estimate a zero/one hurdle beta model, then the route you take should depend on whether you want t…

It’s on the list but of course depends on brms release schedule. At present though it works fine with most brms functions if you use the provided code.

Zero-One Inflated Beta Model and Syntax brms

General

Peter_Clayson September 13, 2021, 8:30pm 3

I recommend checking out these brms specific resources: here and here.

Good luck!
Peter

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Zero-One Inflated Beta Model and Syntax brms

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