2 項進行中

115-1 選課時程

進行中

  • 初選第一階段 6/15 – 6/18
  • 初選第二階段 6/22 – 6/25
  • 校際選修 進行中 8/24 – 9/18
  • 初選第三階段 8/31 – 9/3
  • 開學後加退選 進行中 9/7 – 9/21
  • 逾期加退選 9/21 – 9/24
選課資源

加入行事曆

選擇訂閱 Google Calendar,或下載通用的 ICS 檔案。

使用 Google Calendar 時,Google 會收到這份課表的公開連結。

長期追蹤資料分析

Longitudinal Data Analysis

學期
112-2
學分
0 學分
當期課號
536903
永久課號
SCIS30073
開課單位
統計學研究所
授課教師
黃冠華
類別
選修
上課時間表
週一
5
13:20–14:10
長期追蹤資料分析
A406
3 節連堂
6
14:20–15:10
7
15:30–16:20

* 根據陽明交大上課時間表所列

概述

Longitudinal data consist of multiple measures over time on an individual. This type of data occurs extensively in both observational and experimental biomedical studies, as well as in studies in sociology and applied economics. This course will provide an introduction to the principals and methods for the analysis of longitudinal data. While some theoretical statistical detail is given (at the level of appropriate for a Master's student in Statistics), the primary focus will be on data analysis and interpretation. The objects of his course are: . To identify features of longitudinal data and explain the roles of longitudinal data in studying real data phenomenon. . To use a generalized linear model to make inferences about the relationship between responses and explanatory variables while accounting for the correlation among repeated responses for an individual. . To use marginal, random effects, or transition models for longitudinal data when the repeated observations are binary, count, or Gaussian/non-Gaussian continuous. . To familiarize the usage of statistical software implementing these longitudinal data analytic methodologies. . To provide references for your future research.

先修科目

Students are expected to have background on undergraduate probability, and mathematical statistics. Some knowledge on (generalized) linear regression will be helpful.

備註

無備註

教學方式

Course web page: https://ghuang.stat.nycu.edu.tw/course/lda24/

評分方式

The course grade will be based on 4 homework assignments (50%), 1 midterm exam (20%), and 1 final exam (30%).

課程大綱
  • Introduction and examples of longitudinal data

    . Introduction and examples . Notation for longitudinal data . Models for longitudinal data

    備註:Reading: ALD Chapter 1\r\n

  • Exploring longitudinal data

    . Exploring longitudinal data . Exploring correlation structure of longitudinal data

    備註:ALD Chapter 3\r\n

  • Linear modes for longitudinal data

    . Introduction, overview and simple example . Correlation models . Inferences . Evaluating covariance models . Sensitivity to covariance/correlation model and robust variance . Exploiting the empirical variance estimator- generalized estimating equations (GEE) . Where have we been?

    備註:ALD Chapter 4\r\n

  • Linear mixed models for longitudinal data

    . Introduction . Linear mixed models for longitudinal data: example . Details of model building: inference . Model evaluation for linear mixed models . Parameterization of random effects . Estimating individual trajectories

    備註:ALD Chapter 4\r\n

  • GLM for longitudinal data

    . Marginal models . Random effects models . Transition models

    備註:ADL Chapters 7, 8, 9, and 10\r\n

週次計畫
週次主題
第 1 週

2024-02-21(三)
第 2 週

2024-02-28(三)
第 3 週

2024-03-06(三)
第 4 週

2024-03-13(三)
第 5 週

2024-03-20(三)
第 6 週

2024-03-27(三)
第 7 週

2024-04-03(三)
第 8 週

2024-04-10(三)
第 9 週

2024-04-17(三)
第 10 週

2024-04-24(三)
第 11 週

2024-05-01(三)
第 12 週

2024-05-08(三)
第 13 週

2024-05-15(三)
第 14 週

2024-05-22(三)
第 15 週

2024-05-29(三)
第 16 週

2024-06-05(三)
教科書

Handouts corresponding to each lecture will be available on the class website before each class. Reading assignments are from the following book: . Diggle PJ, Heagerty P, Liang KY and Zeger SL (2002). Analysis of Longitudinal Data, 2nd edition. Oxford University Press. (ALD)

Office Hours
地點
A423 Joint Education Hall (my office)
時間
By appointment
聯絡方式
Email: ghuang@nycu.edu.tw