課程資訊

Statistical Analysis for Repeated Measurements

111-2

EPM5003

849 U0320

2.0

(智財問題恕不開放旁聽) (本課程 1-13 週為「非同步遠距教學」，5/25 與 6/1 期末口頭報告為「同步 (或非同步) 遠距教學」，如同學不克同步參與，可以預錄方式先將約 25 分鐘的口頭報告 mp4 預錄檔上傳到 NTU COOL 作業區)

In Biomedical field, we usually need to deal with longitudinal data. The conventional generalized linear models cannot be used because of ignoring the dependence among measurements. In this course, we will introduce random effects models, mixed effects models, generalized estimating equations (GEEs), generalized mixed effects models (GLMMs), and transition models. In addition to statistical modeling, we also teach how to use SAS or R to analyze the complicated longitudinal data.

(智財問題恕不開放旁聽) (本課程 1-13 週為「非同步遠距教學」，5/25 與 6/1 期末口頭報告為「同步 (或非同步) 遠距教學」，如同學不克同步參與，可以預錄方式先將約 25 分鐘的口頭報告 mp4 預錄檔上傳到 NTU COOL 作業區)

In each topic, we will start from a real data application, learn how to use SAS or R to analyze the data, and then we will teach the theoretical parts. Students will learn both the statistical theory and real data analysis.

(智財問題恕不開放旁聽) (本課程 1-13 週為「非同步遠距教學」，5/25 與 6/1 期末口頭報告為「同步 (或非同步) 遠距教學」，如同學不克同步參與，可以預錄方式先將約 25 分鐘的口頭報告 mp4 預錄檔上傳到 NTU COOL 作業區)

(生物)統計學或流行病學等相關基礎課程。

Prerequisite course: at least one biostatistics (or statistics) or epidemiology course.

Office Hours

1. Analysis of Correlated Data with SAS and R, 3rd edition. Shoukri, M. M. and
Chaudhary M. A. (2007). Chapman & Hall/CRC.
2. Diggle, P.J., Heagerty, P.J., Liang, K.Y., & Zeger, S.L. (2002). Analysis
of Longitudinal Data. 2nd Ed. Oxford University Press.

(僅供參考)

 No. 項目 百分比 說明 1. 作業 50% Assignments and homework (will be adjusted after considering the grade distribution of the whole class.) 2. 期末報告 50% Final report

 上課形式 以錄影輔助 作業繳交方式 考試形式 其他
 課程進度
 週次 日期 單元主題 第1週 2/23 重複測量與相依性資料導論 (Introduction to repeated measurements and correlated data) 第2週 3/2 隨機效應模式 (Random effects models) 第3週 3/9 混合效應模式 (Mixed effects model:G-side analysis) 第4週 3/16 混合效應模式 II (Mixed effects model: G-side analysis II) 第5週 3/23 混合效應模式 III (Mixed effects model: statistical inference for regression parameters) 第6週 3/30 Mixed effects model：R-side analysis 第7週 4/6 重複測量之模式診斷 (Diagnostics for repeated measurements) 第8週 4/13 廣義線性模式 (Generalized linear model) 第9週 4/20 廣義估計方程式(GEE)之統計推論 (Statistical inference in GEE) 第10週 4/27 廣義估計方程式(GEE)之穩健變異數估計 (The robust variance estimator in GEE) 第11週 5/4 廣義線性混合模式 I (Generalized linear mixed model I) 第12週 5/11 廣義線性混合模式 II (Generalized linear mixed model II) 第13週 5/18 轉移模式 (Transition model) 第14週 5/25 文獻討論-GEE vs. GLMM (請單數號同學預先準備slides與25分鐘的報告，並於中午12點前將slides存成pdf檔上傳至作業區) (Paper discussion: Generalized estimating equations and generalized linear mixed-effects models for modelling resource selection) 第15週 6/1 文獻討論-Transition Model vs. Mixed Effects Model (請雙數號同學預先準備slides與25分鐘的報告，並於中午12點前將slides存成pdf檔上傳至作業區) (Paper discussion: Predicting hemoglobin levels in whole blood donors using transition models and mixed effects models) 第16週 6/8 Final exam week (no class)