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| 베이지안 t-검정× | 순차 분석 (그룹 순차 설계)× | |
|---|---|---|
| 분야≠ | 베이지안 | 통계학 |
| 계열≠ | Bayesian methods | Hypothesis test |
| 기원 연도≠ | 2009 | 1977 |
| 창시자≠ | Rouder, Speckman, Sun, Morey & Iverson | P. C. O'Brien & T. R. Fleming; P. C. Pocock |
| 유형≠ | Bayesian hypothesis test | Sequential / adaptive hypothesis test |
| 원전≠ | Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D. & Iverson, G. (2009). Bayesian t Tests for Accepting and Rejecting the Null Hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237. DOI ↗ | O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556. DOI ↗ |
| 별칭≠ | bayesian two-sample t-test, bayes factor t-test, Bayesçi t-Testi | sequential testing, group sequential design, interim analysis, Sıralı Analiz (Sequential Testing / Group Sequential Design) |
| 관련 | 5 | 5 |
| 요약≠ | The Bayesian t-test, formalised by Rouder and colleagues in 2009, is a two-group comparison method that works within a Bayesian framework. Instead of a p-value, it produces a Bayes Factor (BF₁₀) that quantifies the evidence the data provide for the alternative hypothesis relative to the null, and it reports the full posterior distribution of the standardised effect size δ with a highest-density interval. | 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. |
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