手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| ベイズ的検出力分析(保証)× | 逐次分析(群逐次計画)× | |
|---|---|---|
| 分野 | 統計学 | 統計学 |
| 系統 | Hypothesis test | Hypothesis test |
| 提唱年≠ | 1986 | 1977 |
| 提唱者≠ | Spiegelhalter & Freedman (1986); O'Hagan, Stevens & Campbell (2005) | P. C. O'Brien & T. R. Fleming; P. C. Pocock |
| 種類≠ | Bayesian sample size determination | Sequential / adaptive hypothesis test |
| 原典≠ | O'Hagan, A., Stevens, J.W. & Campbell, M.J. (2005). Assurance in Clinical Trial Design. Pharmaceutical Statistics, 4(3), 187–201. DOI ↗ | O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556. DOI ↗ |
| 別名 | assurance, bayesian sample size determination, bayesian assurance, Bayesian Güç Analizi (Assurance / Bayesian Sample Size) | sequential testing, group sequential design, interim analysis, Sıralı Analiz (Sequential Testing / Group Sequential Design) |
| 関連≠ | 3 | 5 |
| 概要≠ | Bayesian power analysis — also called assurance — is a sample size determination method that replaces the frequentist notion of power with a probability-weighted average over a prior distribution on the effect size. First formalised by Spiegelhalter and Freedman (1986) and further developed by O'Hagan, Stevens and Campbell (2005), it answers the question: given our current uncertainty about the true effect, what sample size gives us a high overall probability of obtaining a statistically significant result? | Sequential analysis is a framework for conducting hypothesis tests with pre-planned interim looks at accumulating data, allowing a study to stop early for efficacy or futility while controlling the overall Type I error rate. The group sequential approach was formalised by Pocock (1977) and O'Brien and Fleming (1979), and remains the standard for confirmatory clinical trials and rigorous A/B experiments. |
| ScholarGateデータセット ↗ |
|
|