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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/97871


    Title: 熱卡插補法應用於成就測驗不完整作答反應之推估研究
    Other Titles: A Study of Inferring Feasibility in Item Non-Response of Achievement Tests by Using the Hot Deck Imputation Method
    Authors: 林曉芳
    Keywords: 成就測驗 ; 不完整作答反應 ; 熱卡插補法
    Achievement test ; Item non-response ; Hot deck imputation method
    Date: 2003-09
    Issue Date: 2016-06-13 11:11:20 (UTC+8)
    Abstract: 本研究之主要動機為探討成就測驗中學生的不完整作答反應，是否能利用插補方法，對不完整作答反應資料進行彌補。研究者藉由試題參數與受試者能力參數的分析討論，期望能獲得支持插補技術應用於成就測驗的結論。研究探討的問題有三：（一）利用統計插補法所估算之替代值與實際作答反應之間是否有差異存在；（二）受試者之部份答題反應組型在經過插補後，與完全作答反應組型之參數分析結果是否有差異存在；（三）能否將統計插補技術應用於成就測驗模式中。 本研究程序包含兩部份，一為模擬資料的分析，模擬研究主要作為實證研究結果的驗證與推論；另一個則為實證資料的分析與討論。根據研究結果與討論，提出以下幾點歸納結論：（一）插補後資料的分布型態：當缺失比例不大時，能府何原本的資料分布假設，但隨著缺失比例愈高，且高至30%以上時，已漸不符合原本假設；（二）熱卡法應用於不同樣本大小、不同缺失比例之成就測驗，其試題參數與受試者能力參數估計結果之差異：當缺失比例愈高時，各項參數之估計標準差值幾乎是最大的；若忽略未作答反應之受試者的表現時，其分析所得的參數估計值亦並未是最佳的，反而是將所有受試者的作答反應進行插補估計後，所得的參數估計標準差值才是最小、最佳的；（三）熱卡插補技術應用於成就測驗之可行性：經過模擬研究與實證資料的分析後，證明熱卡法所推估的未作答反應，與直接刪除未作答反應或不處理未作答反應的確有差異存在，且經過插補所產生的替代值，對於受試者的能力表現能提供更穩定有效的解釋力。
    The purpose of this study is to infer the likelihood of examinees’ item non-responses being made up, by using an imputation method in item non-response or missing values in achievement tests. The research design contains two procedures: One is simulation research, and the other is pragmatic research. Hot deck imputation method is the main concern method used in this research.<bra>The results are as follows: 1.The distribution of below 30% percent item non-response data after imputation is the same as the original data, but following the higher percentages of item non-response, the distribution does not match what we expected. 2.Applying the hot deck imputation method to the achievement test with different sample sizes and different percentages of item non-response, the researcher found that following the higher percentages of item non-responses in any sample sizes, a higher standard deviation occurred. Besides, ignoring or deleting these item non-responses is not a food way to deal with this test response pattern. Imputating an appropriate answer for the item non-responses by the hot deck imputation method, we could get the least standard deviation of the test and ability parameters estimation, and also get the most test information from examinees. 3.Based on the above discussion, this study suggested that Hot deck imputation method could cope with item non-responses in achievement tests fairly well.
    Relation: 教育與心理研究, 26(3),527-555
    Journal of Education & Psychology
    Data Type: article
    Appears in Collections:[教育與心理研究 TSSCI] 期刊論文

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