生物統計模式與資料分析
Biostatistical modelling and data analysis
| 節 | 週三 |
|---|---|
5 13:20–14:10 | 生物統計模式與資料分析 YT305 2 節連堂 |
6 14:20–15:10 |
* 根據陽明交大上課時間表所列
本課程介紹生物統計模式與資料分析的核心概念與方法。對連續、離散、存活反應等資料，課程涵蓋多元迴歸、羅吉斯迴歸、線性判別分析及存活分析。存活分析包括 Kaplan-Meier 曲線、Log-rank 檢定、Cox 模型，以及多重存活事件與競爭風險資料分析。課程結合統計軟體（R）實作。 This course introduces the core concepts and methods of biostatistical modeling and data analysis. For continuous, discrete, or survival response data, the course covers multiple linear regression, logistic regression, linear discriminant analysis, and survival analysis. Survival analysis includes Kaplan-Meier estimation, log-rank tests, Cox models, and the analysis of multiple survival outcomes and competing risks data. Hands-on implementation using R software is also included.
30% 出席/課堂參與/隨堂考/作業，35%期中考，35%期末考
| 週次 | 主題 |
|---|---|
| 第 1 週 | 1 2 Introduction & Review of Basic Statistics |
| 第 2 週 | 3 Multiple regression |
| 第 3 週 | 3 Multiple regression & Lab |
| 第 4 週 | 3 Removing Linear/Additive Assumption |
| 第 5 週 | 4 Logistic regression |
| 第 6 週 | 4 Logistic regression & Lab |
| 第 7 週 | 4 Linear Discriminant Analysis |
| 第 8 週 | Mid exam |
| 第 9 週 | 1 2 Survival analysis |
| 第 10 週 | 3 Kaplan-Meier estimator for survival function |
| 第 11 週 | 4 Log-rank test for comparing two survivals |
| 第 12 週 | 5 6 7 Cox regression models & Lab |
| 第 13 週 | 8 Time-dependent covariates |
| 第 14 週 | 9 Multiple survival outcomes |
| 第 15 週 | 9 Competing risks data* & Lab |
| 第 16 週 | Final exam |
1. R for Basic Biostatistics in Medical Research, 2024, Anand Srinivasan, Archana Mishra, Praveen Kumar-M 2. Survival Analysis: Techniques for Censored and Truncated Data (2003) Klein and Moeschberger
- 地點
- 醫學二館211
- 時間
- Email預約
- 聯絡方式
- ccwen@nycu.edu.tw