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效应值
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在統計學中,效應值(英語:effect size,或譯效果量)是量化現象強度的數值。效應值實際的統計量包括了兩個變數間的相關程度、迴歸模型中的迴歸係數、不同處理間平均值的差異……等等。無論哪種效應值,其絕對值越大表示效應越強,也就是現象越明顯。效應值與特效检验的概念是互補的。在估算統計檢定力、需要的樣本數與進行元分析時,效應值經常扮演重要角色。
在研究結果中給出效應值被視為恰當的或必須的。相對於統計學上的顯著性,效應值有利於了解研究結果的強度。特別是在社會科學和醫學研究上,效應值更顯得重要。絕對與相對效應值可以傳遞不同的訊息,又可互相補充訊息。有個心理學的研究學會鼓勵學者給出效應值:
報告主要結果時必須一併報導效應值……如果測量值的單位在實際面上是有意義的(例如每人每日抽煙的香煙根數),則我們建議採用非標準化的效應值(例如迴歸係數或平均值差異)而不是標準化的效應值(例如相關係數)。
— L. Wilkinson and APA Task Force on Statistical Inference (1999, p. 599)
在比較平均數的情況下,效應值經常指的就是實驗結束後,實驗組與對照組之間「標準化後的平均差異程度」,依照慣例,效應值可解讀為以下幾個程度:
效應值 | d | r |
---|---|---|
較小 | 0.2 | 0.10 |
中等 | 0.5 | 0.30 |
較大 | 0.8 | 0.50 |
參考文獻
延伸閱讀
- Aaron, B., Kromrey, J. D., & Ferron, J. M. (1998, November). Equating r-based and d-based effect-size indices: Problems with a commonly recommended formula. Paper presented at the annual meeting of the Florida Educational Research Association, Orlando, FL. (ERIC Document Reproduction Service No. ED433353)
- Bonett, D. G. Confidence intervals for standardized linear contrasts of means. Psychological Methods. 2008, 13: 99–109. doi:10.1037/1082-989x.13.2.99.
- Bonett, D. G. Estimating standardized linear contrasts of means with desired precision. Psychological Methods. 2009, 14: 1–5. doi:10.1037/a0014270.
- Brooks, M.E.; Dalal, D.K.; Nolan, K.P. Are common language effect sizes easier to understand than traditional effect sizes?. Journal of Applied Psychology. 2013. doi:10.1037/a0034745.
- Cumming, G.; Finch, S. A primer on the understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions. Educational and Psychological Measurement. 2001, 61: 530–572.
- Imdadullah, M. (2014). Effect Size for dependent Sample t test. itfeature.com document on Effect Size for dependent Sample t test (页面存档备份,存于互联网档案馆)
- Kelley, K. Confidence intervals for standardized effect sizes: Theory, application, and implementation. Journal of Statistical Software. 2007, 20 (8): 1–24 [2016-11-14]. (原始内容存档于2015-09-13).
- Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Sage: Thousand Oaks, CA.
- Sawilowsky, Shlomo S. (2003). A Different Future For Social And Behavioral Science Research, Journal of Modern Applied Statistical Methods, Vol 2(1), 128-132.
外部連結
維基學院中的相關研究或學習資源:效应值 |
線上應用
- Copylefted Effect Size Confidence Interval R Code with RWeb service for t-test, ANOVA, regression, and RMSEA
- Online calculator for computing different effect sizes like Cohen's d, r, q, f, d from dependent t tests and transformation of different measures of effect size (页面存档备份,存于互联网档案馆)
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