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Pmap 8521 5 Dags And Potential Outcomes 1 Do Ing Observational Causal Inference

Pmap 8521 5 Dags And Potential Outcomes 1 Do Ing Observational Causal Inference

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Benzer Videolar

1.
PMAP 8521 • (5) DAGs and potential outcomes: (1) do()ing observational causal inference
 29:35
2.
PMAP 8521 • (5) DAGs and potential outcomes: (0) Introduction
 1:12
3.
PMAP 8521 • Example: Matching and IPW with R: 5: Inverse probability weighting
 20:37
4.
PMAP 8521 • (12) IV II + RDD II: (1) Treatment effects and compliance
 42:40
5.
PMAP 8521 • Instrumental variables 5: Instrumental variables with R
 46:35
6.
PMAP 8521 • (1) Evaluation and the causal revolution: (2.2) Evidence, evaluation, and causation
 19:36
7.
PMAP 8521 • (5) DAGs and potential outcomes: (2) Potential outcomes
 45:31
8.
PMAP 8521 • Example: Instrumental variables with R: 5: Checking instrument validity (real data)
 13:01
9.
PMAP 8521 • Example: Diff-in-diff with R: 5: Diff-in-diff with regression
 8:45
10.
PMAP 8521 • Example: DAGs with Dagitty
 12:30
11.
PMAP 8521 • Example: Regression discontinuity with R: 5: Measuring the gap parametrically
 13:37
12.
PMAP 8521 • (6) Threats to validity: (2) Statistical conclusion validity
 18:03
13.
PMAP 8521 • Example: Regression discontinuity with R: 2: Sharp or fuzzy?
 10:49
14.
PMAP 8521 • Example: Regression with R
 54:00
15.
PMAP 8521 • Example: Instrumental variables with R: 7: Validity + 2SLS (real data)
 12:39
16.
PMAP 8521 • Example: Diff-in-diff with R: 2: Load and clean data
 9:04
17.
PMAP 8521 • (8/9) Difference-in-differences I & II: (0) Introduction
 2:35
18.
PMAP 8521 • Regression discontinuity 2: Arbitrary cutoffs & causal inference
 23:52
19.
PMAP 8521 • Instrumental variables 6: Treatment effects & compliance
 59:28
20.
PMAP 8521 • (13) Choosing and planning ethical evaluations: (2) Model- and design-based inference
 24:38
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