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README.Rmd

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* [04 Using Propensity Scores](https://causal-inference-r-workshop.netlify.app/04-using-pscores.html)
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* [05 Checking Propensity Scores](https://causal-inference-r-workshop.netlify.app/05-pscore-diagnostics.html)
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* [06 Fitting the outcome model](https://causal-inference-r-workshop.netlify.app/06-outcome-model.html)
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* [07 G-Computation](https://causal-inference-r-workshop.netlify.app/07-g-computation.html)
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* [08 Tipping Point Sensitivity Analyses](https://causal-inference-r-workshop.netlify.app/08-tipr.html)
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### Installing materials locally
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README.md

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### Slides
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- [00
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- [00
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Intro](https://causal-inference-r-workshop.netlify.app/00-intro.html)
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- [01 Whole
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- [01 Whole
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Game](https://causal-inference-r-workshop.netlify.app/01-causal_modeling_whole_game.html)
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- [02 Causal
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- [02 Causal
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Diagrams](https://causal-inference-r-workshop.netlify.app/02-dags.html)
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- [03 Introduction to Propensity
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- [03 Introduction to Propensity
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Scores](https://causal-inference-r-workshop.netlify.app/03-pscores.html)
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- [04 Using Propensity
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- [04 Using Propensity
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Scores](https://causal-inference-r-workshop.netlify.app/04-using-pscores.html)
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- [05 Checking Propensity
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- [05 Checking Propensity
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Scores](https://causal-inference-r-workshop.netlify.app/05-pscore-diagnostics.html)
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- [06 Fitting the outcome
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- [06 Fitting the outcome
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model](https://causal-inference-r-workshop.netlify.app/06-outcome-model.html)
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- [07
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G-Computation](https://causal-inference-r-workshop.netlify.app/07-g-computation.html)
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- [08 Tipping Point Sensitivity
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Analyses](https://causal-inference-r-workshop.netlify.app/08-tipr.html)
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### Installing materials locally
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We will be using RStudio Cloud for the workshop, but if you would like
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to install the required packages and course materials, we have an R
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package called
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{[causalworkshop](https://github.com/malcolmbarrett/causalworkshop)} to
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help you do that\! You can install
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help you do that! You can install
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{[causalworkshop](https://github.com/malcolmbarrett/causalworkshop)}
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from GitHub with:
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slides/00-intro.html

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# Causal Inference in R: Introduction
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### 2020-07-29 (updated: 2020-12-01)
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### 2020-07-29 (updated: 2021-08-30)
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&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;svg style="height:0.8em;top:.04em;position:relative;" viewBox="0 0 496 512"&gt;&lt;path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"/&gt;&lt;/svg&gt; [https://www.malco.io/](https://www.malco.io/)
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&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; <svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"/></svg> [https://www.malco.io/](https://www.malco.io/)
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slides/01-causal_modeling_whole_game.Rmd

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title: "Causal Modeling in R: Whole Game"
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# Causal Modeling in R: Whole Game
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### Teladoc Health
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