Summary analysis of random samples
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- r
- Domain
- data, data-visualization
Research direction
No files, tests, or entry points are named. Start by inspecting the repository for the existing random-sample analyses and their outcome outputs; define the summary boundary before implementing it. Done should include variability estimates across samples, forest-plot visualizations, and empirical-Bayes and full-Bayes meta-analytic results.
Written by the indexing model from the issue text.
Description
As a researcher I want to get an estimate of the variability of the results if random sampling is replicated.
If the analyses of the individual random samples of a virtual cohort have been performed, a summary analysis of all random samples should be possible. This analysis should target the variability between the individual random samples from the same virtual cohort. The results of the simulated results will summary by outcome using meta-analytic techniques that target the variability of the results under different parametrization settings. Visualization techniques using forest plots will be applied and analytical techniques using Empirical Bayes and full Bayes meta-analysis will be used.
- Dominant language
- R
- Stars
- 2
- Forks
- 0
- PR merge metrics
- No merged PRs in 30d
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- 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.
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