課程資訊
課程名稱
結構方程模式
Structural Equation Modeling 
開課學期
103-2 
授課對象
公共衛生學院  流預所流行病學組  
授課教師
杜裕康 
課號
EPM7001 
課程識別碼
849EM0850 
班次
 
學分
全/半年
半年 
必/選修
選修 
上課時間
星期五3,4(10:20~12:10) 
上課地點
公衛214 
備註
本課程以英語授課。與陳雅美合開
總人數上限:30人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1032EPM7001_SEM_2015 
課程簡介影片
 
核心能力關聯
本課程尚未建立核心能力關連
課程大綱
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課程概述

The aim of this course is to provide a general introduction to path analysis, factor analysis, structural equation modeling and multilevel analysis. The examples and data are extensively drawn from literature in health and medical sciences. Students will learn how to use Mplus and Lisrel software to undertake these analyses. After attending the course, students should be able to describe the relationship between commonly used statistical methods and structural equation modeling (SEM); define the statistical concepts behind factor analysis, path analysis, and structural equation modeling; understand the relation between SEM and multilevel modeling (MLM); explain the above statistical methods and properly interpret their results; and use a computer software package to undertake the statistical analyses and correctly specify the statistical models. SEM has been very popular among quantitative social scientists in the last two decades, and has started to draw attentions from epidemiologists. SEM is a very useful tool for testing causal models, and learning SEM theory is very helpful for students to understand the causal assumptions behind different models. SEM is also useful for explaining the concepts of confounding, mediation and moderation in epidemiological research. The course will start with basic concepts of SEM, such as model specification, fitness testing, interpretation of causality and model modification. Then, more advanced topics will be introduced, such as equivalence models, identification issues, and multiple groups testing. MLM will then be introduced for the analysis of clustered data, where random effects may be viewed as latent variables. Students will be assessed by their participation in the classroom discussion, one interim and one final report on the critical appraisal of literature and real data analysis.  

課程目標
By the end of this course, students should be able to:
• Describe the relations between general linear models and structural equation models
• Explain the statistical theory of principal component analysis, exploratory and confirmatory factor analysis, path analysis and structural equation models
• Understand the concepts and rationales of causal models within the framework of structural equation models
• Understand the concept of mediation and the decomposition of total effects into direct and indirect effects
• Undertake structural equation modeling using statistical software packages and interpret the results properly
• Report the results from structural equation modeling properly
 
課程要求
Active participation in class discussion and practical session is required. 
預期每週課後學習時數
 
Office Hours
另約時間 
指定閱讀
• Journal articles
• Rex Kline: Principles and Practices in Structural Equation Modeling. Guilford, 2011.
• Randall Schumacher, Richard Lomax. A beginner’s Guide to Structural Equation Modeling. Routledge, 2010.
• Joop Hox: Multilevel analysis. Routledge, 2010.
• Yu-Kang Tu, Darren Greenwood. Modern Methods for Epidemiology. Springer, 2012.
 
參考書目
• David Kaplan: Structural equation modeling: foundations and extensions. Sage: Los Angeles, CA, 2009.
• Kenneth Bollen, Patrick J Curran. Latent curve models: a structural equation perspective. Wiley: Hoboken, New Jersey, 2006.
 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
第1週
  Lecture: Directed acyclic graphs and path analysis (杜裕康) 
第2週
  Lecture: Principle component analysis and factor analysis (杜裕康) 
第3週
  Lecture: Confirmatory factor analysis (杜裕康) 
第4週
  Lecture: Structural equation models (杜裕康) 
第5週
  國際學術交流 
第6週
  Practical: Using Mplus for path analysis & confirmatory factor analysis (杜裕康) 
第7週
  溫書假 
第8週
  Practical: Using Mplus for structural equation models (杜裕康) 
第9週
  Lecture: Case studies in structural equation models (陳雅美) 
第10週
  Lecture: Issues about structural equation modeling (陳雅美) 
第11週
  Practical: Using Lisrel for structural equation modeling (1) (陳雅美) 
第12週
  Practical: Using Lisrel for structural equation modeling (2) (陳雅美) 
第13週
  Lecture: latent growth curve modeling (1) (杜裕康) 
第14週
  Lecture: latent growth curve modeling (2) (杜裕康) 
第15週
  Practical: Using Mplus for latent growth curve modeling (杜裕康) 
第16週
  Final student presentation (杜裕康 陳雅美) 
第17週
  端午節