課程信息
30,625 次近期查看

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為25 小時

建議:5 weeks of study, 3-5 hours per week...

英語(English)

字幕:英語(English)

您將獲得的技能

Instrumental VariablePropensity Score MatchingCausal InferenceCausality

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為25 小時

建議:5 weeks of study, 3-5 hours per week...

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 3 小時

Welcome and Introduction to Causal Effects

This module focuses on defining causal effects using potential outcomes. A key distinction is made between setting/manipulating values and conditioning on variables. Key causal identifying assumptions are also introduced.

...
8 個視頻 (總計 128 分鐘), 3 個測驗
8 個視頻
Hypothetical interventions17分鐘
Causal effects19分鐘
Causal assumptions18分鐘
Stratification23分鐘
Incident user and active comparator designs14分鐘
3 個練習
Practice Quiz4分鐘
Practice Quiz4分鐘
Causal effects18分鐘
2
完成時間為 2 小時

Confounding and Directed Acyclic Graphs (DAGs)

This module introduces directed acyclic graphs. By understanding various rules about these graphs, learners can identify whether a set of variables is sufficient to control for confounding.

...
8 個視頻 (總計 86 分鐘), 2 個測驗
8 個視頻
Paths and associations7分鐘
Conditional independence (d-separation)13分鐘
Confounding revisited9分鐘
Backdoor path criterion15分鐘
Disjunctive cause criterion9分鐘
2 個練習
Practice Quiz8分鐘
Identify from DAGs sufficient sets of confounders22分鐘
3
完成時間為 4 小時

Matching and Propensity Scores

An overview of matching methods for estimating causal effects is presented, including matching directly on confounders and matching on the propensity score. The ideas are illustrated with data analysis examples in R.

...
12 個視頻 (總計 171 分鐘), 5 個測驗
12 個視頻
Greedy (nearest-neighbor) matching17分鐘
Optimal matching10分鐘
Assessing balance11分鐘
Analyzing data after matching20分鐘
Sensitivity analysis10分鐘
Data example in R16分鐘
Propensity scores11分鐘
Propensity score matching14分鐘
Propensity score matching in R15分鐘
5 個練習
Practice Quiz6分鐘
Practice Quiz8分鐘
Matching12分鐘
Propensity score matching10分鐘
Data analysis project - analyze data in R using propensity score matching16分鐘
4
完成時間為 3 小時

Inverse Probability of Treatment Weighting (IPTW)

Inverse probability of treatment weighting, as a method to estimate causal effects, is introduced. The ideas are illustrated with an IPTW data analysis in R.

...
9 個視頻 (總計 119 分鐘), 3 個測驗
9 個視頻
IPTW estimation11分鐘
Assessing balance9分鐘
Distribution of weights9分鐘
Remedies for large weights13分鐘
Doubly robust estimators15分鐘
Data example in R26分鐘
3 個練習
Practice Quiz6分鐘
IPTW18分鐘
Data analysis project - carry out an IPTW causal analysis8分鐘
4.7
43 個審閱Chevron Right

50%

完成這些課程後已開始新的職業生涯

23%

通過此課程獲得實實在在的工作福利

來自A Crash Course in Causality: Inferring Causal Effects from Observational Data的熱門評論

創建者 MFDec 28th 2017

I really enjoyed this course, the pace could be more even in parts. Sometimes the pace could be more even and some more books/reference material for further study would be nice.

創建者 FFNov 30th 2017

The material is great. Just wished the professor was more active in the discussion forum. Have not showed up in the forum for weeks. At least there should be a TA or something.

講師

Avatar

Jason A. Roy, Ph.D.

Professor of Biostatistics
Department of Biostatistics and Epidemiology

關於 宾夕法尼亚大学

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies. ...

常見問題

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您购买证书后,将有权访问所有课程材料,包括评分作业。完成课程后,您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

還有其他問題嗎?請訪問 學生幫助中心