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    題名: 欠值重複交叉實驗設計之分析
    其他題名: Analysis of Missing Data for Replicate Crossover Design
    作者: 邵軍 ; 周賢忠 ; 林慧
    Shao, Jun;Chow, Shein-Chung;Ju, Huey L.
    貢獻者: 統計系
    關鍵詞: 二元交叉實驗設計;有效性;不完整資料;樣本大小;人體內差異
    Dual crossover;Efficiency;Incomplete data;Sample size;Within-subject variability
    日期: 1995-06
    上傳時間: 2014-06-04 12:23:50 (UTC+8)
    摘要: 在這篇論文中,我們考慮了非完整二序列二元交叉實驗設計 (incomplete two sequence dual crossover design) 的統計推論。我們推導出人體內差異(within subject variabilities) 在相等及不等的條件下,處理 (treatment) 的有效估計值及其t統計量。這個研究結果顯示在人體內差異相等的情況時,我們可獲得精確 (exact)的有限樣本結果。反之,在人體內差異不等時,精確有限樣本結果則無法求之。然而,在溫和的條件 (mild condition)下,我們建立一些有限樣本的精確結果及大樣本結果。
    Statistical inference on the effect of two treatments, based on incomplete data from a two-sequence dual crossover design, is considered. Efficient estimates of the treatment effect and the corresponding t- type statistics are derived for both cases of equal and unequal within-subject variabilities. In the case of equal within-subject variability, exact results for finite samples are obtained. When within-subject variabilities are unequal, there may exist no exact finite sample results. Under mild conditions, some exact finite sample results and some large sample results are established.
    關聯: 中國統計學報,33(2),215-233
    資料類型: article
    顯示於類別:[統計學系] 期刊論文

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