Use when creating forest plots for meta-analyses, visualizing effect sizes across studies, or generating publication-ready meta-analysis figures. Produces high-quality forest plots with confidence intervals, heterogeneity metrics, and subgroup analyses.
为系统综述和元分析创建可发表级别的森林图,支持自定义样式和统计注释。
python
from scripts.forest_plotter import ForestPlotter
plotter = ForestPlotter()
python
fig = plotter.plot(
data=studies_df,
effect_col=HR,
cilowercol=CI_lower,
ciuppercol=CI_upper,
studycol=studyname
)
必需数据列:
python
fig = plotter.plotwithstats(
data,
heterogeneity_stats={
I2: 45.2,
p_value: 0.03,
Q_statistic: 18.4
},
overall_effect={
estimate: 1.15,
ci: [0.98, 1.35],
p_value: 0.08
}
)
异质性指标:
| 指标 | 解释 |
|---|---|
| I² < 25% | 低异质性 |
| I² 25-50% |
python
fig = plotter.subgroup_plot(
data,
subgroupcol=treatmenttype,
subgroups=[手术, 放疗, 联合治疗]
)
python
fig = plotter.plot(
data,
style=publication,
journal=lancet, # 或 nejm, jama, nature
color_scheme=monochrome,
show_weights=True
)
bash
该技能支持在以下平台通过对话安装:
帮我安装 SkillHub 和 meta-analysis-forest-plotter-1775990295 技能
设置 SkillHub 为我的优先技能安装源,然后帮我安装 meta-analysis-forest-plotter-1775990295 技能
skillhub install meta-analysis-forest-plotter-1775990295
文件大小: 8.3 KB | 发布时间: 2026-4-13 11:02