Add/update documentation

[ras44]

During Friday's office hours we discussed adding an introduction for new users about meta-learners, propensity modeling, etc. This issue was created to track and collaborate on those updates.

@jeongyoonlee, a couple questions:

• just to confirm, should we focus on edits to the content in docs/*.rst?
• any specific areas that you feel are in need of attention?

Thanks!

[ras44]

Some notes on areas that could possibly use attention:

• About CausalML (https://causalml.readthedocs.io/en/latest/about.html)

  • Is it Causal ML or CausalML?
  • use W for treatment variable for notation consistency
  • Add material on Neural network based algorithms
    • CEVAE
    • dragonnet

• Methodology

  • Perhaps add a section on propensity score, since it is referenced frequently?

  • S-Learner

    • Stage 2
      • Here we fit the model with the entire dataset, including the treatment flag as a covariate
      • Possibly modify: 'Including the treatment propensity score...`
      • Perhaps "When the control and treatment groups have very different outcomes with respect to the covariates..."

  • T-Learner

    • In other words: we fit two models, each using the data from one of the two possible outcomes
    • define response under control, response under treatment \mu_0 and \mu_1

  • X-Learner

    • perhaps a high level intro mentioning the fact that X-Learners generate two estimates for CATE and then take a weighted average

  • R-Learner

    • add detail from Nie and Wager's paper

  • ... will continue to add

• Installation

  • consider one single source of truth (currently this is replicated in README.md and the docs)
  • consider putting all install instructions in a separate markdown document that can include screenshots (helpful for the windows install)
    • using *.rst requires uploads of images into the repo, which bloats the repo size and is cumbersome
    • referencing, adding images, and editing a markdown within GitHub is relatively easy
    • possible to add docs/installation.md?

• Examples

  • consider replacing all code chunks and images with links to jupyter notebooks or other sections

• Interpretable Causal ML

  • consider replacing all code chunks and images with links to jupyter notebooks or other sections

[jeongyoonlee]

Thanks for taking the lead on this, @ras44.

To answer some of the questions:

• docs/*.rst will be our main documentation published to readthedocs, while README.md will host a subset of instructions for installation and quick start examples.
• Let's use CausalML to refer to the package.
• I agree that we should use consistent variable naming conventions. e.g., W for treatment assignment

I will add more later.

[rolandrmgservices]

https://econml.azurewebsites.net/spec/flowchart.html

https://docs.readthedocs.io/en/stable/guides/jupyter.html

[paullo0106]

@jeongyoonlee reference to the User guide Flowchart we created in KDD 2021 tutorial, inspired by EconML's flowchart

• Source: KDD 2021 - Introduction to CausalML - page 41 and 42 in this slide, the slide doesn't look public anymore maybe due to updates in Uber org's gsuite permission

[ras44]

hi @paullo0106 would it be possible to share a higher-res/sharper version of that second screenshot? I was hoping to add it to the documentation 🙏