Review of 'Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes'

Phillip J. Schulte, Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian

By Joowon Lee in Causal Inference

October 5, 2022

R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

You can embed an R code chunk like this:

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00
fit <- lm(dist ~ speed, data = cars)
fit
## 
## Call:
## lm(formula = dist ~ speed, data = cars)
## 
## Coefficients:
## (Intercept)        speed  
##     -17.579        3.932

Including Plots

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par(mar = c(0, 1, 0, 1))
pie(
  c(280, 60, 20),
  c('Sky', 'Sunny side of pyramid', 'Shady side of pyramid'),
  col = c('#0292D8', '#F7EA39', '#C4B632'),
  init.angle = -50, border = NA
)
A fancy pie chart.

Figure 1: A fancy pie chart.

Posted on:
October 5, 2022
Length:
1 minute read, 159 words
Categories:
Causal Inference
Tags:
Causal Inference Dynamic Treatment Regime
See Also:
Review of 'Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes'