進行多層次建模最小可行的樣本數建議:貝氏模擬取向

Sample Size Requirements of Using Multilevel Models: Bayesian Simulation Study

曾明基
Ming-Chi Tseng

Doi:10.3966/181665042017121304001


所屬期刊: 第13卷第4期 「教育心理,輔導與測評」
主編:國立臺灣師範大學教育心理與輔導學系兼任教授
林世華
系統編號: vol051_01
主題: 測驗與評量
出版年份: 2017
作者: 曾明基
作者(英文): Ming-Chi Tseng
論文名稱: 進行多層次建模最小可行的樣本數建議:貝氏模擬取向
論文名稱(英文): Sample Size Requirements of Using Multilevel Models: Bayesian Simulation Study
共同作者:
最高學歷:
校院名稱:
系所名稱:
語文別: 中文
論文頁數: 26
中文關鍵字: 貝氏方法; 多層次模型; 成長模型
英文關鍵字: Bayesian method; multilevel model; growth model
服務單位: 國立東華大學師資培育中心
稿件字數: 13119
作者專長: 心理計量
投稿日期: 2016/6/7
論文下載: pdf檔案icon
摘要(中文): 本研究經由模擬研究的方式同時比較貝氏方法和ML 估計法在多層次模型以
及成長模型建構時,最小可行的分析樣本單位數,並同時考慮存在隨機遺漏下,
在多層次模型以及成長模型建構所需的樣本數調整。研究發現,使用貝氏方法進
行多層次模型以及成長模型建構,所需的樣本數較小且可以獲得穩定的參數覆蓋
率以及統計考驗力,值得加以推廣。
摘要(英文): This paper shows practical guidelines of sample size requirements when results are
analyzed by multilevel models. The study found that when Bayesian method is used for
multilevel model,stable parameters and power are attained through fewer samples.
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