課程名稱 |
生物統計與流行病學原理 Principles of Biostatistics and Epidemiology |
開課學期 |
108-1 |
授課對象 |
公共衛生學院 全球衛生碩士學位學程 |
授課教師 |
林先和 |
課號 |
MGH7003 |
課程識別碼 |
853EM0030 |
班次 |
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學分 |
2.0 |
全/半年 |
半年 |
必/選修 |
必修 |
上課時間 |
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上課地點 |
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備註 |
初選不開放。本課程以英語授課。601B教室.時間:1-9,8/26~9/2.合授教師:英文授課.僅限MGH學生修課與溫在弘、洪 弘合授 總人數上限:18人 外系人數限制:2人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1081MGH7003_ |
課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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課程概述 |
The aim of this course is to introduce concepts of study design, data collection, and statistical analysis commonly used in public health research with a focus on the application in public health practice. This course includes three parts: The first part is “study design”, which gives an introduction of causal inference and the principle of study design. The second part is “analytical method”, which gives an introduction on data analyses and the applications of statistical method. The third part is critical appraisal of public health literatures. Examples from Taiwan unique research topics are given and illustrated in the course.
For lab data analyses, some example datasets will be provided to students. Students will perform statistical analyses using these datasets. We will mainly use R program for class discussion.
For lab data analyses, some example datasets will be provided to students. Students will perform statistical analyses using these datasets. We will mainly use R program for class discussion.
For lab data analyses, some example datasets will be provided to students. Students will perform statistical analyses using these datasets. We will mainly use R program for class discussion. The TA will demonstrate the R code and provide the answers for specific topics.
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課程目標 |
At the end of the course students should have the following core knowledge and competencies:
1. To understand the principle of statistical and causal inference.
2. To explain how random variation and bias affect public health research findings.
3. To understand the principle of study design in experimental and observational studies.
4. To critically appraise public health literature in terms of validity and applicability.
5. To analyze health dataset using statistical software. |
課程要求 |
Students should read and review the reading material before and after the lecture. The slides of each lecture will be available on the course for students to download. This course includes lectures for critical appraisal. Students need to download the papers from CEIBA for paper critique |
預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
參考書目
References
1. Aviva Petrie, and Caroline Sabin (2009). Medical Statistics at a Glance, 3rd edition.
Wiley-Blackwell.
2. Kenneth J. Rothman (2012). Epidemiology: An Introduction. 2nd edition. Oxford
University Press.
3. Hernán MA, Robins JM (2019). Causal Inference. Boca Raton: Chapman & Hall/CRC,
forthcoming.
4. Marcello Pagano and Kimberlee Gauvreau (2007). Principles of Biostatistics. 2nd
edition. Brooks/Cole. |
評量方式 (僅供參考) |
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週次 |
日期 |
單元主題 |
Week 1 |
Aug 26 (Morning) |
Introduction of the course
Measuring disease occurrence and descriptive epidemiology (Lin) |
Week 2 |
Aug 27 (Morning) |
Introduction
Descriptive statistics (mean/sd, box plot)
Probability models
Estimation (mean)
Sampling distribution (Hung) |
Week 3 |
Aug 27 (Afternoon) |
Causal inference
Experimental studies (Lin) |
Week 4 |
Aug 28 (Morning) |
Estimation (CI)
Hypothesis testing (Hung) |
Week 5 |
Aug 28 (Afternoon) |
Observational studies
Cohort studies
Bias and random error (Lin) |
Week 6 |
Aug 29 (Morning) |
Correlation
GLM (Hung) |
Week 7 |
Aug 29 (Afternoon) |
Confounding bias revisit
Intermediate variable
Effect modification (Lin) |
Week 8 |
Sep 2 (Morning) |
Spatial epidemiology and disease mapping (Wen) |
Week 9 |
Sep 2 (Afternoon) |
Critical appraisal of public health studies
Evidence synthesis (Lin) |
Week 10 |
Sep 20 |
Final project and report due |