meta-analysisComprehensive R-based meta-analysis skill covering RevMan + Stata equivalents + esc + RVE + Bayesian NMA + survival meta + TSA + single-group meta + diagnostic meta + systematic review workflow; produces forest plots, funnel plots, heterogeneity (I²), publication bias, subgroup analysis, meta-regression, network meta, for a total of 23 analysis figures. All analyses ship reproducible R code. Can also provide meta topic-direction judgment + literature retrieval and organization + screening + data-extraction functionality. / 基于 R 的全方位 Meta 分析技能,覆盖 RevMan + Stata 等价 + esc + RVE + 贝叶斯 NMA + 生存 Meta + TSA + 单组率 Meta + 诊断 Meta + 系统评价流程;输出森林图、漏斗图、异质性(I²)、发表偏倚、亚组分析、元回归、网络 Meta等共 23 种分析图形。所有分析提供可复现 R 代码。还可提供Meta选题方向判断 + 文献检索整理 + 筛选 + 数据提取功能。
Install via ClawdBot CLI:
clawdbot install medstatstar/meta-analysisGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
send → https://ct-meta.coze.site/runPotentially destructive shell commands in tool definitions
eval (Calls external URL not in known-safe list
https://github.com/medstatstar/meta-analysisUses known external API (expected, informational)
ncbi.nlm.nih.govGenerated Sep 5, 2026
Researchers can input study data (e.g., effect sizes, sample sizes) and obtain pooled estimates, forest plots, and heterogeneity metrics (I²) with fully reproducible R code. This streamlines systematic reviews and meta-analyses for clinical trials, saving weeks of manual work.
For researchers preparing manuscripts for journals, the skill generates publication-ready forest plots, funnel plots, and subgroup analyses that meet common reporting standards. It also supports language auto-switching to produce analysis reports in Chinese or English, catering to international journals.
Instructors can use the skill to teach meta-analysis methodologies by running live code examples and visualizations. It offers a full-featured environment covering advanced topics like network meta-analysis and diagnostic test accuracy, enhancing hands-on learning.
This skill assists in synthesizing evidence for drug efficacy and safety from multiple trials, supporting regulatory submissions, health technology assessments, and internal decision-making. Bayesian NMA capabilities allow indirect comparisons of treatment options.
Policy analysts and guideline panels can use the skill to perform comprehensive meta-analyses, including risk of bias assessment and sensitivity analyses, to inform clinical guidelines and public health policies. The TSA module helps determine sample size sufficiency in accumulating evidence.
Offer the meta-analysis skill as part of a cloud-based biostatistics platform, charging subscription fees for access to the advanced analytics modules. Revenue comes from recurring subscription fees, potentially tiered by features (e.g., basic vs. advanced NMA), for researchers and institutions.
Enable users to pay for individual meta-analysis runs without committing to a subscription. Revenue is generated per successful analysis (e.g., cost per submitted query or report), providing flexibility for occasional users.
Leverage the skill's capability to provide tailored meta-analysis services for pharmaceutical companies, academic groups, or CROs. Consultants use the tool to deliver high-quality analyses and reports, charging a project-based fee.
💬 Integration Tip
Integrate data import from common sources (e.g., CSV exports from RevMan or Excel) to reduce manual entry; ensure compliance with data privacy regulations when handling patient-level data.
Scored Sep 5, 2026
Audited Sep 5, 2026 · audit v1.0
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