查詢結果分析
來源資料
頁籤選單縮合
題 名 | 效應量集中與分散程度之多層次整合性分析=Multi-level Meta-analysis of Central Tendency and Variability of Effect Sizes |
---|---|
作 者 | 洪來發; 王文中; | 書刊名 | 測驗年刊 |
卷 期 | 46:2 1999.07[民88.07] |
頁 次 | 頁61-72 |
分類號 | 319 |
關鍵詞 | 整合性分析; 多層次分析; 效應量; 分散; 集中趨勢; 經驗貝氏估計; Meta-analysis; Multi-level analysis; Effect sizes; Variability; Central tendency; Empirical Bayes estimates; |
語 文 | 中文(Chinese) |
中文摘要 | 有鑑於傳統的整合性分析只考慮單一層次和效應量的集中趨勢,本研究提出多層次的整合性分析,同時探應效應量的集中和分散情形。多層次模式較能貼切資料的結構,避免因為模式錯誤所產生的統計偏誤。而分析效應量的分?情形,可以更具體看出影響效應量分?的原因和預測因子,除有助整合性分析外,也可提供後續實驗操弄的建議。我們介紹了適用於整合性分析的多層次模式,以及參數估計方法和意義。最後透過簡單例子,呈現此一分析方法的應用的意涵。 |
英文摘要 | Conventional meta-analysis is uni-level and focuses on central tendency of effect sizes. In this study, we propose multi-level meta-analysis that can explore both central tendency and variability of effect sizes. Multi-level analysis better reflects hierarchy of data structures and thus avoids statistical bias due to model mis-specification. Analysis of variability of effect sizes better depicts influencing factors on the variability, which not only is helpful to meta-analysis but also gives suggestions for further research design. We propose several sub-models for meta-analysis and explain estimation procedures and meanings of the parameters. Through real data analysis, implications and applications of the proposed analysis are addressed. |
本系統中英文摘要資訊取自各篇刊載內容。