Multilevel Meta-Analysis
Two- or three-level models for dependent effect sizes nested within studies or labs.
- 方法族
- Meta-analysis
- 引擎
- metafor 5.0.1 (R)
何时使用
当你有一张效应表并需要可辩护的汇总估计时使用。
将元分析从计算器输出中取出，绑定到一条决策轨迹：效应量、异质性、模型选择与来源。
可生成的图形
- 森林图
局限与适用范围
- 结果取决于您提供的研究、语料与参数，以及所选模型。该分析按所报告的方式汇总证据，并不确立因果关系。
- 每幅图形均标明其来源，且每次运行均可依据相同的输入、参数与引擎版本逐位复现。
本方法族内
- Univariate Meta-AnalysisPool one effect size per study into a single summary estimate with heterogeneity diagnostics.
- GLMM Meta-AnalysisGeneralised linear mixed models for binary/count outcomes without normal approximation.
- Network Meta-AnalysisMixed treatment comparison across ≥3 interventions with a connected evidence network.
- Diagnostic Test AccuracyBivariate sensitivity/specificity model with a summary ROC curve.
- Dose–Response Meta-AnalysisModel the shape of an exposure–outcome relationship across dose levels.
- P-Uniform*Bias-corrected effect estimate robust to selective publication.
- P-Curve AnalysisTest the significant p-values for evidential value vs p-hacking via the p-curve's right-skew (Simonsohn et al. 2014).
- Trial Sequential AnalysisAdjust cumulative meta-analysis for repeated significance testing — is the evidence conclusive, or is more information needed (Wetterslev et al. 2008)?
- MA Power AnalysisProspective / retrospective power for a meta-analytic design specification.