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Causal Tree Learning For Heterogeneous Treatment Effect Estimation
Given high-dimensional data describing differences in characteristics between individuals, what state-of-the-art ML technique is best suited for…
Jul 30, 2020
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Ken Acquah
3
An UX Update To The Causal Flows Website
I've recently updated my site to to allow readers to more easily access to my blog posts on introductory causal inference.
Jul 6, 2020
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Ken Acquah
1
Estimating Heterogeneous Treatment Effects
Oftentimes, analysts are interested how a particular intervention differentially affects an observed population. How can we estimate the extent of…
Jul 5, 2020
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Ken Acquah
2
June 2020
Propensity Score Matching: What Can Go Wrong?
What are some of the challenges an analyst must be wary of when using propensity score matching for causal inference tasks?
Jun 29, 2020
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Ken Acquah
2
Propensity Score Matching
How do we "control" for a large number of confounding variables when analyzing causal effects in an observational setting, and have very little control…
Jun 21, 2020
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Ken Acquah
4
Confounding Bias
Why is causal inference so hard? What "adjustments" can we make to observational data in order to make it easier?
Jun 14, 2020
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Ken Acquah
2
Estimating Average Treatment Effects
How can we estimate average treatment effects and what biases must we be wary of when evaluating our estimation?
Jun 10, 2020
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Ken Acquah
4
Potential Outcomes Model
Is there a way we describe the extent of causal relationships, in order to more wholly characterize quantifiable effects?
Jun 5, 2020
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Ken Acquah
2
3
May 2020
Structural Causal Models
How do we represent causal relationships between the many interconnected processes which comprise our universe?
May 27, 2020
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Ken Acquah
1
1
Getting In To A Causal Flow
What is causal inference? Why is it useful? How can you use to amplify your decision-making capabilities?
May 22, 2020
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Ken Acquah
6
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