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assignment 等级：入门
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## 关键信息

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timer 56小时总数

## 关于内容

A practical and example filled tour of simple and multiple regression techniques (linear, logistic, and Cox PH) for estimation, adjustment and prediction.

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## 课程大纲

• Week 1 - Introduction and Module 1A: Simple Regression Methods
In this module, a unified structure for simple regression models will be presented, followed by detailed treatises and examples of both simple linear and logistic models.
• Week 2 - Module 1B: More Simple Regression Methods
In this model, more detail is given regarding Cox regression, and it's similarities and differences from the other two regression models from module 1A. The basic structure of the model is detailed, as well as its assumptions, and multiple examples are presen...
• Week 3 - Module 2A: Confounding and Effect Modification (Interaction)
This module, along with module 2B introduces two key concepts in statistics/epidemiology, confounding and effect modification. A relation between an outcome and exposure of interested can be confounded if a another variable (or variables) is associated with b...
• Week 4 - Module 2B: Effect Modification (Interaction
Effect modification (Interaction), unlike confounding, is a phenomenon of "nature" and cannot be controlled by study design choice. However, it can be investigated in a manner similar to that of confounding. This set of lectures will define and give examples...
• Week 5 - Module 3A: Multiple Regression Methods
This module extends linear and logistic methods to allow for the inclusion of multiple predictors in a single regression model.
• Week 6 - Module 3B: More Multiple Regression Methods
This set of lectures extends the techniques debuted in lecture set 3 to allow for multiple predictors of a time-to-event outcome using a single, multivariable regression model.
• Week 7 - Module 4: Additional Topics in Regression

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## 教师

• John McGready - Bloomberg School of Public Health
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## 内容设计师

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
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## 平台

Coursera是一家数字公司，提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作，在线提供一些课程，并提供许多科目的课程，包括：物理，工程，人文，医学，生物学，社会科学，数学，商业，计算机科学，数字营销，数据科学 和其他科目。

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