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eleanormurray/causalgraphs_latex: Drawing graphical models for causal inference ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

eleanormurray/causalgraphs_latex

开源软件地址(OpenSource Url):

https://github.com/eleanormurray/causalgraphs_latex

开源编程语言(OpenSource Language):

TeX 100.0%

开源软件介绍(OpenSource Introduction):

Graphical Models for Causal Inference using LaTeX

This repository contains a handbook for creating the most common types of graphical models used for teaching and thinking about causal inference using LaTeX. This file is available as a pdf handbook which contains explanations, examples, and sample code for creating graphical models for causal inference in LaTeX. The souce .tex file for the handbook is also available in the repository.

These graphical models included in this handbook are:

  1. Directed acyclic graphs (DAGs)
  2. Single-world intervention graphs (SWIGs)
  3. Probability trees for inverse probability weighting
  4. Decision trees for Markov models.
  5. Path diagrams for Structural Equation Models (SEMs).

This handbook was written by me based on LaTeX code I have developed over the past 6 years through a combination of trial and error, and extensive reading of questions and answers on Tex.StackExchange. I hope that the code here will be as helpful for others trying to draw their own graphical causal models as StackExchange has been for me. All suggestions for improvement are welcome and appreciated.




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