菜单
R-native meta-analysis via Harrer et al. (2021) — effect sizes, pooling, forest/funnel plots, heterogeneity, subgroup, meta-regression, publication bias (Egger, trim-and-fill, PET-PEESE, p-curve), NMA, Bayesian MA, SEM-MA, RoB plots, power analysis.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | doing-meta-analysis-r |
| domain | research |
| version | 1.0.0 |
| license | CC0-1.0 |
| language | R |
| description | R-native meta-analysis via Harrer et al. (2021) — effect sizes, pooling, forest/funnel plots, heterogeneity, subgroup, meta-regression, publication bias (Egger, trim-and-fill, PET-PEESE, p-curve), NMA, Bayesian MA, SEM-MA, RoB plots, power analysis. |
| triggers | ["meta-analysis","forest plot","heterogeneity","I-squared","tau-squared","Egger","trim and fill","meta-regression","network meta-analysis","Harrer","dmetar","metafor","systematic review pooling","effect size pooling"] |
| sources | ["https://github.com/MathiasHarrer/Doing-Meta-Analysis-in-R","https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/"] |
| citation | Harrer, M., Cuijpers, P., Furukawa, T.A., & Ebert, D.D. (2021). Doing Meta-Analysis with R: A Hands-On Guide. Chapman & Hall/CRC Press. ISBN 978-0-367-61007-4. |
Canonical reference: Harrer et al. (2021) Doing Meta-Analysis with R: A Hands-On Guide.
Invoke when the user asks for any of: effect-size pooling, forest/funnel plots, heterogeneity diagnostics, subgroup / meta-regression, publication-bias assessment (Egger, trim-and-fill, PET-PEESE, p-curve), network meta-analysis, Bayesian meta-analysis, SEM-MA, RoB plots, or power analysis.
install.packages(c("meta", "metafor", "netmeta", "brms"))
# dmetar is a companion package — bundled with the Harrer book
remotes::install_github("MathiasHarrer/dmetar")
esc / metafor::escalc() to compute effect sizes (SMD, OR, HR, RR).meta::metagen() (generic IV), metabin(), metacont(), metacor().
Default: REML random-effects; report τ², I², prediction interval.meta::forest(), funnel(); save to PDF/PNG at 300 DPI.update.meta(subgroup=), meta-regression via metafor::rma().metabias() (Egger), trimfill(), PET-PEESE (metafor),
p-curve (dmetar::pcurve()).netmeta::netmeta(), SUCRA via netrank().brms::brm(bf(yi | se(sei) ~ 1 + (1|study))).prisma2020-flow-diagram.stipaidevlake/research/<study_id>/) and register metadata in ops.artifacts.meta-analysis-pipeline (orchestration), prisma2020-flow-diagram (reporting).study_id, n1, n2, mean1, mean2, sd1, sd2 (continuous) or
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End-to-end guide for publishing a SaaS offer on Microsoft AppSource/Azure Marketplace. Covers Partner Center setup, offer creation, technical integration, listing content, and certification. Based on Microsoft's Mastering the Marketplace curriculum.
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