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
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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
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
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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
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Causal Flows
Causal Flows
A casual introduction to causal inference for business analytics.

Causal Flows

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