Causal Flows

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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…
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Ken Acquah
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.
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Ken Acquah
Estimating Heterogeneous Treatment Effects
Oftentimes, analysts are interested how a particular intervention differentially affects an observed population. How can we estimate the extent of…
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Ken Acquah

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?
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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…
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Ken Acquah
Confounding Bias
Why is causal inference so hard? What "adjustments" can we make to observational data in order to make it easier?
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Ken Acquah
Estimating Average Treatment Effects
How can we estimate average treatment effects and what biases must we be wary of when evaluating our estimation?
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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?
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Ken Acquah
3

May 2020

Structural Causal Models
How do we represent causal relationships between the many interconnected processes which comprise our universe?
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Ken Acquah
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?
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Ken Acquah
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