政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/99903
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 113311/144292 (79%)
造訪人次 : 50931830      線上人數 : 993
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧：
  • 您可在西文檢索詞彙前後加上"雙引號"，以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋，建議至進階搜尋限定作者欄位，可獲得較完整資料
    •  進階搜尋


    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/99903


    題名: 國中生人際衝突多層次潛在類別Mixture模式分析
    其他題名: Multilevel LCA Mixture Analysis of Interpersonal Conflicts among Middle School Students
    作者: 王郁琮;溫福星
    關鍵詞: 多層次潛在類別分析;多層次Mixture模式;國中生人際衝突
    multilevel latent class analysis;multilevel mixture model;interpersonal conflicts
    日期: 2013-03
    上傳時間: 2016-08-09 16:05:54 (UTC+8)
    摘要: 本研究利用多層次潛在類別無母數模式與多層次Mixture模式，針對國中生人際衝突二元資料同時進行學生及班級多階層類型探索，並對班級衝突脈絡變項進行多階層因素分析。研究樣本來自國中1～3年級85個班級共2,783人。學生層次分析顯示，國中生人際衝突族群分為三類，分別為「行為」、「語言」與「和諧」衝突族群。其中男生較易被歸為「行為」衝突；女生較易被歸為「語言」衝突。班級層次分析顯示，班級特定機率比值為單一類型而班級特定隨機指標建構出單因子模式，但個別因素負荷量不顯著，表示本研究在班級個數有限下，無法區分班級異質性。本研究進一步比較無母數與Mixture模式之分析結果，並針對人際衝突危機的實徵意涵與多層次潛在類別Mixture模式的技術應用進行詳細論述。
    Conventional latent class analysis (LCA) classifies subjects into various categories by analyzing their response patterns to observed variables. However, multilevel latent class analysis (MLCA) is methodologically more appropriate when data are collected from a nested structure sample. Primary strength of MLCA is to analyze student and classroom levels of data simultaneously while taking the nested structure of the data into account. This study utilized and compared two different MLCA approaches including nonparametric MLCA and MLCA mixture models. Gender and proportion of boys in class are level 1 and level 2 covariates, respectively. Data were collected from 85 junior high classes with a total of 2,783 7th to 9th grade students. The observed variables include five binary self-reported survey questions regarding experiences related to interpersonal conflicts at school. All analyses were carried out by using Mplus6.0. Results show that non-parametric MLCA and MLCA mixture models fit the data equally well. Students are clustered into three categories namely "peaceful", "vocal" and "behavioral" of interpersonal conflicts. Boys are more likely to be classified as "behavioral" conflict while girls are more likely to be classified as "vocal" conflict. Nonparametric model clusters level 2 random intercepts as one class, whereas mixture model extracts the covariance among five level 2 random indicators as single factor possibly due to small number of level 2 units. Results of nonparametric and mixture MLCA were also discussed. Empirical implications as well as methodological challenges applying MLCA nonparametric and mixture models, are discussed in the end of the study.
    關聯: 教育與心理研究, 36(1),89-115
    Journal of Education & Psychology
    資料類型: article
    DOI 連結: http://dx.doi.org/10.3966/102498852013033601004
    DOI: 10.3966/102498852013033601004
    顯示於類別:[教育與心理研究 TSSCI] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    36(1)-89-116.pdf9338KbAdobe PDF2714檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋