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研究生:賴驥緯
研究生(外文):Lai, Chi-Wei
論文名稱:Bayesian evaluation of response styles in polytomous data with multiple group factor analysis model
論文名稱(外文):Bayesian evaluation of response styles in polytomous data with multiple group factor analysis model
指導教授:蔡蓉青蔡蓉青引用關係
指導教授(外文):Tsai, Rung-Ching
學位類別:碩士
校院名稱:國立臺灣師範大學
系所名稱:數學系
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:2016
畢業學年度:104
語文別:英文
論文頁數:40
中文關鍵詞:作答風格態度量表多群組離散型因素分析模型貝氏估計貝氏因子
外文關鍵詞:Likert scaleresponse styleBayesian estimationBayes factorinequality constrained hypotheses
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  • 被引用被引用:0
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  • 下載下載:26
  • 收藏至我的研究室書目清單書目收藏:0
本研究之主要目的在於檢定態度量表中,作答者是否受到作答風格而影響問卷之作答,即兩群人是否有作答風格之差異。所謂作答風格乃是當潛在態度相同的兩位作答者可能會因為作答風格的差異,而做出不同的回答。本研究利用了多群組離散型驗證性因素分析模型來分析多群組的有序分類數據,其中利用貝氏估計在最小限制式的條件下,來估計模型中的閾值、潛在因子的平均與變異數以及因素負荷量等結構參數,並且使用Gibbs sampling來估計這些參數的聯合分配。再利用貝氏因子來檢驗李克氏五點量表在兩群組間是否存在作答風格差異。於本研究中,透過模擬所得之結果顯示,貝氏因子可用來檢定極端、默認肯定及默認否定等作答風格。本研究中分析「1998 年國際資訊科技教育應用研究 (SITES 1998)」之跨國五點量表問卷,選取其中來自法國及義大利的作答者,分析對於資訊融入教學的學習成效認同程度。其中,義大利的作答者相對於法國之作答者具有默認肯定之作答風格。
The main purpose of this study is to use Bayesian estimation and Bayes factor to test for response styles in polytomous data using multiple group categorical confirmatory factor analysis model. Joint Bayesian estimates of the thresholds, the factor means and variances, as well as the factor loadings using Gibbs sampling are proposed subjected to some minimal identifiability constraints. Bayes factor is used to test hypotheses of different types of response styles with their corresponding inequality constraints among the thresholds. Our simulation studies show that Bayes factor is effective in testing for different types of response styles. Analysis of an international comparative research suggests that Italy, despite having similar mean attitude, exhibits the acquiescent response style on how much they think information and communication technology improve the student's achievement or ability compared to France.
1 Introduction 5
2 Multiple group categorical CFA model 7
3 Bayesian estimation 9
3.1 Conditional distributions of parameters 11
3.1.1 Y 's conditional distribution 11
3.1.2 's conditional distribution 12
3.1.3 F's conditional distribution 12
3.1.4 's conditional distribution 13
3.1.5 's conditional distribution 14
3.1.6 's conditional distribution 15
3.2 Convergence criteria 16
4 Bayes factors 17
4.1 Denition 17
4.2 Extreme response style (ERS) 19
4.3 Mid-point response style (MRS) 19
4.4 Acquiescent response style (ARS) 19
4.5 Disacquiescent response style (DARS) 20
5 Simulation study 20
5.1 Parameters setting 21
5.2 starting value 22
5.3 Results 23
6 Real data 23
6.1 Results 25
7 Discussion 28
8 Conclusion 34

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