n_obs(..., disaggregate = TRUE) for brms models with `trials()` or `weights()`
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Enhancement :boom:
- Dominant language
- R
- Stars
- 442
- Forks
- 47
- Avg merge
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- Merged PRs (30d)
- 7
Description
For binomial and multinomial trials with a | trials() or | weights() argument, there should be an option to get disaggregate the data and return the total number of trials, like we do with 'glm' models.
library(brms)
m <- brm(incidence | trials(size) ~ period, data = lme4::cbpp, family = "binomial")
n_obs(m)
n_obs(m, disaggregate = TRUE)
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First steps
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- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the R implementation of n_obs() and its existing disaggregate handling for glm models. Trace how brms models with trials() or weights() are represented, then make disaggregate = TRUE return the total number of trials for binomial and multinomial models, matching the requested examples.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- data
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100