跳到主要內容

臺灣博碩士論文加值系統

(18.97.9.172) 您好!臺灣時間:2025/02/18 05:44
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:李梅琪
研究生(外文):Mei-Chi Li
論文名稱:邏輯斯模型加隨機反應模型之複合模型對於配對資料之應用與探討
論文名稱(外文):Hybrid Logistic Regression and Random-Response Model in a Matched Pairs Study
指導教授:吳建華吳建華引用關係
指導教授(外文):Chien-Hua Wu
學位類別:碩士
校院名稱:中原大學
系所名稱:應用數學研究所
學門:數學及統計學門
學類:數學學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:中文
論文頁數:40
中文關鍵詞:配對資料隨機反應模型基線類組邏輯斯模型
外文關鍵詞:random-response modelbaseline-category logit modelmatched pairs data
相關次數:
  • 被引用被引用:0
  • 點閱點閱:181
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
對於兩相關樣本,亦即在第一個樣本裡的觀測值都與第二個樣本裡的觀測值相關,若每個觀察值只有2個選項時,2 × 2列聯表即可表達此種資料型態,這個研究方法是分析配對資料(matched pairs data)的二維機率表,以統計方法判斷選項之改變率在第一樣本與第二樣本是否一致(McNemar (1947))。然而,在抽樣調查裡,當人們在接受比較敏感的問題時,通常都會拒絕回答或是給一個不正確的答案。大多數的人都不會直接回答敏感性政治問題,例如:在319槍擊案之後,你是否改變你所支持的候選人。然而S. L. Warner (1965)提出隨機反應模型(random-response model)來解決此敏感性問題所產生的有偏估計值(bias),但此方法只討論受訪者回答一個問題的情況,而此篇論文在於討論受訪者回答兩個問題的統計方法。首先,母體裡的受訪者隨機分配到A群或B群裡,而且母體裡的每一個人不是在A群裡就是在B群裡,A群的問卷與B群的問卷問題不同,訪談者不知受訪者接受那群的問卷。我們利用此類方法來估計比較敏感問題的配對樣本機率,A群與B群的訪談問題各有2項,受訪者只需對每項問題回答"是"或"否",並勿需直接回答問題,亦即將隨機反應模型裡的兩張卡片各一個問題,延伸為兩張卡片各兩個問題,借此間接問卷得到我們想估計參數的估計值。此研究方法目的有二:(1)檢定事件發生後的機率值是否會有改變。(2)更進一步,我們用到基本類別的基線類組邏輯斯模型(baseline-category logit model)來了解反應變數是否會受到自變數的影響。
For two dependent samples, each observation in one sample pairs with an observation in the other sample. A two-way table having the same categories for both classifications summarizes such data. This proposal presents analyses of square contingency tables with matched pairs data. However, in survey sampling, persons being interviewed often refuse to answer or give correct answer to sensitive questions that may embarrass them or be harmful to them in some way. For instance, some persons may not respond truthfully to political questions such as, "Did you change your mind in the presidential election in Taiwan after the 319 gun shot?" The method was first proposed by S. L. Warner (1965) called the random-response model. Designate the people in the population who have or do not have the characteristic of interest as groups A and B, respectively. Thus each person in the population is in either group A or group B answered only one question. We present a method of estimating the proportion of people who have some characteristic of interest without obtaining direct answers from the people interviewed with matched pairs data and then test its difference. Furthermore, the baseline-category logit model is introduced as well to see if there is any substantial difference between two groups as the independent variable changes along increase its units.
1 緒論
2 文獻探討
2.1 隨機反應模型(Random-Response Model)
2.1.1 Warner's 模型(Model)
2.1.2 屬質的隨機反應資料(Random-Response for Qualitative Data)
2.1.3 屬量的隨機反應資料(Random-Response for Quantitative Data)
2.2 配對資料(Matched Pairs Data)
3 研究方法
3.1 研究方法及參數估計
3.2 檢定統計量
3.3 基線類組邏輯斯模型(Baseline-Category Logit Model)
4 實例分析
4.1 估計參數
4.2 檢定統計量
4.3 基線類組邏輯斯模型(Baseline-Category Logit Model)
5 結論
參考文獻
附件
1 Agresti, A. (1996) "An Introduction to Categorical Data Analysis" New York: Wiley.
2 Agresti, A. (2002) "Categorical Data Analysis" New York: Wiley.
3 Abul-Ela, A.-L., Greenberg, B. G., and Horvitz, D. G. (1967) "A multi-proportions randomized response model" Journal of the American Statistical Association, 62, 990-1008.
4 Eriksson, S. A. (1973) "A new model for randomized response" International Statistical Review, 41, 101-113.
5 Greenberg, B. G., Abul-Ela, A.-L., Simmons, W. R., and Horvitz, D. G. (1969) "The unrelated question randomized response model: Theoretical framework" Journal of the American Statistical Association, 64, 520-539.
6 Greenberg, B. G., Kuebler, R. R., Jr., Abernathy, J. R., and Horvitz, D. G. (1971) "Application of the randomized response technique in obtaining quantitative data" Journal of the American Statistical Association, 66, 243-250.
7 McNemar, Q. (1947) "Note on the sampling error of the difference between correlated proportions or percentages" Psychometrika, 12, 153-157.
8 Scheaffer, R. L., Mendenhall, W. and Ott, L. (1990) "Elementary Survey Sampling" Boston: Pws-Kent.
9 Scheers, N. J., and Dayton, C. Mitchell (1988) "Covariate randomized response models" Journal of the American Statistical Association, 83, 969-974.
10 Warner, S. L. (1965) "Randomized response: A survey technique for eliminating evasive answer bias" Journal of the American Statistical Association, 60, 63-69.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top