菜单
Explain why different studies reach different conclusions — heterogeneity investigation protocol. Budget: 30 studies, 30 effect sizes, 50 web searches.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
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。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill heterogeneity-investigation命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | heterogeneity-investigation |
| description | Explain why different studies reach different conclusions — heterogeneity investigation protocol. Budget: 30 studies, 30 effect sizes, 50 web searches. |
| dependencies | {"tactics":["effect-size-extraction","evidence-synthesis-planning","quality-assessment-protocol"],"sops":["data-extraction-form","effect-size-planning","heterogeneity-source-analysis","inclusion-criteria-design","meta-analysis-synthesis","pico-formulation","publication-bias-assessment","risk-of-bias-assessment","sensitivity-analysis-design"]} |
Design a protocol to investigate and explain between-study heterogeneity — why studies of the same question reach different conclusions.
When a meta-analysis reveals substantial heterogeneity (I2 > 50%, significant Q-test, large tau2), this strategy designs the investigation protocol: subgroup analyses, meta-regression, moderator identification, and outlier diagnostics. Produces the investigation plan, not the computation.
| Resource | Floor | Target |
|---|---|---|
| Studies identified | 20 | 30 |
| Effect sizes extracted | 20 | 30 |
| Web searches | 35 | 50 |
| Moderator candidates | 5 | 10+ |
| Quality assessments | 15 | 30 |
Budget gate: cannot exit until 80% of floor met.
<HARD-GATE>
| Metric | Current | Floor | Target | Status |
|--------|---------|-------|--------|--------|
| Studies found | 0 | 20 | 30 | BLOCKED |
| Effect sizes planned | 0 | 20 | 30 | BLOCKED |
| Web searches done | 0 | 35 | 50 | BLOCKED |
| Moderators identified | 0 | 5 | 10+ | BLOCKED |
| Quality assessed | 0 | 15 | 30 | BLOCKED |
</HARD-GATE>
| Tactic | When to Use |
|---|---|
| effect-size-extraction | Extract effect sizes with full study characteristics |
| quality-assessment-protocol | Assess whether quality explains heterogeneity |
| evidence-synthesis-planning | Plan subgroup and meta-regression models |
| SOP | When to Use |
|---|---|
| pico-formulation | Frame the heterogeneity question |
| inclusion-criteria-design | Broad inclusion to capture variation |
| effect-size-planning | Standardize for comparability |
| data-extraction-form | Rich moderator variable extraction |
| risk-of-bias-assessment | RoB as potential moderator |
| heterogeneity-source-analysis | Core SOP — classify heterogeneity sources |
| sensitivity-analysis-design | Outlier removal, influence diagnostics |
| publication-bias-assessment | Bias as heterogeneity source |
| meta-analysis-synthesis | Final investigation protocol |
pico-formulation emphasizing variation in P/I/C/Oinclusion-criteria-design with broad criteria (capture variation)effect-size-extraction with rich study-level covariatesheterogeneity-source-analysis to generate moderator hypothesesquality-assessment-protocol (RoB as moderator)evidence-synthesis-planning for subgroup + meta-regressionmeta-analysis-synthesis for investigation protocolWeb searches focus on domain knowledge about why results might differ (methodological, clinical, statistical heterogeneity).
protocol:
question: [Why do studies of X reach different conclusions?]
heterogeneity_metrics: [I2, tau2, Q-test, prediction interval]
moderator_candidates:
clinical: [population, intervention details, outcome timing]
methodological: [study design, RoB, measurement tools]
statistical: [effect size type, analysis method, sample size]
investigation_plan:
subgroup_analyses: [categorical moderators]
meta_regression: [continuous moderators]
outlier_diagnostics: [influence analysis, Baujat plot]
sensitivity: [leave-one-out, cumulative by quality]
a_priori_hypotheses: [pre-specified moderator hypotheses]
multiple_testing: [correction strategy]
reporting: PRISMA-2020 + heterogeneity reporting guidelines
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| effect-size-extraction | Systematically extract effect sizes and conditions from papers for meta-analytic synthesis |
| evidence-synthesis-planning | Plan the statistical synthesis approach — model selection, heterogeneity strategy, and reporting |
| quality-assessment-protocol | Methodological quality and bias risk assessment of included studies using validated tools |
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| data-extraction-form | Design structured data extraction form for systematic meta-analysis data collection |
| effect-size-planning | Determine effect size types and calculation methods for meta-analytic synthesis |
| heterogeneity-source-analysis | Identify and classify sources of between-study heterogeneity (clinical, methodological, statistical) |
| inclusion-criteria-design | Define inclusion/exclusion criteria for systematic study selection in meta-analysis |
| meta-analysis-synthesis | Produce final meta-analysis protocol document assembling all planning outputs into PRISMA-compliant protocol |
| pico-formulation | Construct PICO/PECO framework for the meta-analysis research question |
| publication-bias-assessment | Plan funnel plots, Egger's test, trim-and-fill, p-curve, and selection model analyses for publication bias |
| risk-of-bias-assessment | Assess methodological bias using RoB2, PROBAST, or QUADAS-2 validated tools |
| sensitivity-analysis-design | Design leave-one-out, influence diagnostics, subgroup analyses, and robustness checks |