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篇  名 單一受試者研究分析中應用 C 統計量之適切性探討
並列篇名 The Inappropriateness for Applying C Statistic in the Analysis of Single-subject Research
作  者 林冠群 ; 林惠賢
發表期刊 測驗學刊
出版年份 2013 年
卷  期 60 卷 3 期
頁  次 p.569~598
關鍵字 C統計量 ; 一階自相關 ; 分段迴歸 ; 單一受試者研究 ; 斷裂時間系列分析 ; C-statistic ; first-order autocorrelation ; interrupted time series analysis ; segment regression ; single-subject research
語言別 中文
中文摘要

C 統計量是目前在分析單一受試者研究資料時,使用較多的統計分析方法。由理論探討與虛擬案例分析可知, C 統計量主要在衡量小樣本序列資料的一階自相關趨勢,但仍需注意首尾兩筆資料的偏離對 C 統計量的影響。如果研究者不只是想要知道,單一受試者觀察資料是否具有一階自相關趣勢時,還想要知道某種介入是否會造成水準或斜率的改變,此時應用 C 統計量便不適切。因此,建議研究者日後在單一受試者研究中,應避免採用 C 統計量,而改探其他適當分析方法,諸如斷裂時間時深入系列分析,或在能捕捉誤差系列相關之模式中執行分段迴歸法等,才能更適切與深入地探討單一受試者的觀察資料。

英文摘要

Currently, C statistic is the statistical analysis method often used for analyzing the single-subject research data. C statistic mainly measures the first-order autocorrelation trend of the small-sample series of data by theory study and simulation case analysis, but it still needs to pay attention to the influence on C statistic due to deviation of the two data in the initial and the last points. If in a single-subject study the researchers want to know not only whether the first-order autocorrelation trend of the observed data exists, but also whether the intervention causes a change of a level or slope, applying C statistic will be inappropriate. Therefore it suggested that in future single-subject studies the researchers use other appropriate methods, such as interrupted time series analysis or segment regression analysis executed in a model that can catch the serial correlation of errors, rather than C statistic to more appropriately and deeply explore the observed data of a single-subject.

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