spima: Simulated Pseudo-Individual Data Meta-Analysis with ABC-SMC
Meta-analysis via Approximate Bayesian Computation
Sequential Monte Carlo (ABC-SMC) by simulating pseudo-individual
data from published group-level summary statistics. Handles binary,
continuous, and generic effect-size outcomes within a one-stage
mixed-model framework. Supports subgroup analysis.
| Version: |
0.2.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
lme4, parallel, stats, methods, Rcpp |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
ggplot2, testthat, knitr, rmarkdown |
| Published: |
2026-05-28 |
| DOI: |
10.32614/CRAN.package.spima (may not be active yet) |
| Author: |
Yu Haichuan [aut, cre, cph] |
| Maintainer: |
Yu Haichuan <yuhaichuan at whu.edu.cn> |
| BugReports: |
https://github.com/HaichuanYu0703/SPIMA/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/HaichuanYu0703/SPIMA |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Citation: |
spima citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
spima results |
Documentation:
Downloads:
Linking:
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