課程資訊

Statistical Thinking

104-2

EPM5001

849 U0300

Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1042EPM5001_ST105

It is essential for graduate students to develop critical thinking in order to identify caveat in current research, develop new approaches to existing research problems and explore new horizon in their research fields. Students would find it very helpful, if real examples in clinical and epidemiological research are used to demonstrate how to achieve these goals, and this is the aim of this course. The syllabus of this course will loosely follow the order of chapters in my new book of the same title published by Chapman & Hall this summer with supplementary materials. Two tools to promote understanding of statistical modelling will be first introduced: vector geometry for linear models and the directed acyclic graphs for causal thinking. Then, background knowledge will be provided for students to identify the potential caveats and to use their previous knowledge to choose the most appropriate approaches or to develop new approaches. Potential scenarios and examples used in this course include:
• Testing the relation between baseline and changes
• The use of ratio variables in regression analysis
• Statistical methods for testing differences in changes in randomised controlled trials
• Lord’s paradox and the adjustment of baseline values in observational studies
• The problem of collinearity in linear models
• Testing statistical and biological interaction
• Confounding, causality and Simpson’s paradox
• Reversal paradox and the adjustment of intermediate variables on a causal pathway
• Testing direct, indirect and total effects
Students will be asked to give presentations to discuss the reading materials and lead discussion. Students’ performance will be assessed by their participation in the classroom discussion, their presentations and the final essays on one of the topics discussed in the course.

By the end of this course, students should be able to:
• Describe the rationales of directed acyclic graphs in causal inference
• Describe how to use vector geometry to represent linear models
• Describe the problems with mathematical coupling in testing associations between variables
• Explain the problem of regression to the mean with assessing the impact of baseline measurements on changes from baseline
• Explain the potential problems caused by imbalance in baseline covariates in assessing group differences in changes from baseline
• Describe the strength and limitations in methods for adjusting baseline imbalance
• Describe the conceptual relations between biological and statistical interaction
• Explain the causes and potential solutions to the problem of reversal paradox
• Explain the different approaches to separate direct and indirect effects and their underlying assumptions

Students are required to do a mid-term and final presentation on their projects and submit final group project at the end of the course.

Office Hours

• Journal articles
• Yu-Kang Tu, Mark Gilthorpe: “Statistical Thinking in Epidemiology”. Chapman & Hall, 2012.

• Judea Pearl. “Causality” 2nd edition. Cambridge University Press, 2010.
• Bjorn Andersen. Methodological errors in medical research. London: Blackwell, 2000.
• Steven Sloman. “Causal Models”. Oxford University Press, 2005.

(僅供參考)

 No. 項目 百分比 說明 1. class participation 20% 2. oral presentation 30% 3. final exam 20% 4. written report 30%

 課程進度
 週次 日期 單元主題 第1週 02/22 What is “statistical thinking”? 杜裕康 第2週 02/29 補假 第3週 03/07 Causation and directed acyclic graphs (1) 第4週 03/14 Causation and directed acyclic graphs (2) 第5週 03/21 Vector geometry for linear models 第6週 03/28 Why is randomized controlled trial the “gold standard”? 第7週 04/04 放假 第8週 04/11 Lord’s paradox and Simpson’s paradox 第9週 04/18 Regression to the mean 第10週 04/25 Propensity scores 第11週 05/02 Instrumental variables (1) 第12週 05/09 Instrumental variables (2) 第13週 05/16 Regression discontinuity design (1) 第14週 05/23 Regression discontinuity design (2) 第15週 05/30 Student presentation (1) 第16週 06/06 Student presentation (2) 第17週 06/13 Student presentation (3) 第18週 06/20 Student presentation (4)