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Causal Inference in R: A book!

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- [ ] Include D'Agostino^3 plots (#147) - [ ] Discuss HTEs in general: ATT, ATE, ATC the same when no HTE. May be other variables important for HTE -...

:chart_with_upwards_trend: modeling
:book: theory
:dart: target trial

https://rpubs.com/danilofreire/synth https://github.com/google/CausalImpact https://bookdown.org/mike/data_analysis/synthetic-control.html

- [ ] https://pubmed.ncbi.nlm.nih.gov/33791189/ - [ ] https://github.com/eleanormurray/DiD_Tutorial/blob/main/R/Code_DiD_tutorial.R - [ ] https://diff.healthpolicydatascience.org/ - [ ] with marginaleffects: https://marginaleffects.com/bonus/hypothesis.html#difference-in-differences

:chart_with_upwards_trend: modeling
:pencil2: writing

:chart_with_upwards_trend: modeling
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- [ ] #35 - [ ] Maybe focus on RCTs/AB tests as IV analysis - [ ] example in brms: https://rpsychologist.com/adherence-analysis-IV-brms Possible useful: https://www.notion.so/1a897b8106ca44eeaf31dcd5ae5a61b1?v=ff7dc75862c6427eb4243e91836e077e

:chart_with_upwards_trend: modeling
:pencil2: writing

I am working through an example with an instrument -- is there a way to tell `ggdag_adjustment_set()` that I have an instrument? I tried something like this: ``` dagify( x...

:arrow_right: : DAGs

Similar to https://www.tmwr.org/ames.html - [ ] #42

:bar_chart: data
:pencil2: writing

https://ctml.berkeley.edu/introduction-causal-inference

:chart_with_upwards_trend: modeling
:pencil2: writing