In psuthaharan/bandit2arm: Modeling Behavior from the Two-Armed Bandit Task

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

The goal of bandit2arm is to educate users on how to simulate behavioral data obtained from the two-armed bandit task and, subsequently, take the simulated data and estimate the behavior that generated the data.

Installation

You can install the released version of bandit2arm from CRAN with:

install.packages("bandit2arm")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("psuthaharan/bandit2arm")

Simulation

Imagine you are a clinical psychologist - an individual who is passionate about understanding human behavior. You have this amazing task called the two-armed bandit task and you are excited to get participants to try it out! This task contains 200 trials and your goal is to recruit 100 participants:

library(bandit2arm)
## generate 100 individuals who completed the task
# dataset1 contains behavioral data keeping only those selected-choice trials
dataset1 <- simulate_bandit2arm(n_subj = 100, n_tr = 200, trials.unique = TRUE)

# dataset2 contains behavioral data keeping all trials (selected-choice and the non-selected-choice)
dataset2 <- simulate_bandit2arm(n_subj = 100, n_tr = 200, trials.unique = FALSE)

Plot

A month goes by and you have behavioral data from 100 participants. Let's see how some of these individuals performed!

# for plotting purpose - let's use dataset2
# You randomly select a few participant data to observe their behavior

# Participant 100
# View first 10 rows of data
head(dataset2$bandit2arm[[100]],10)
# Visualize behavior 
plot_bandit2arm(data = dataset2, subj = 100, colors = c("orange","purple"))

# Participant 65
# View first 10 rows of data
head(dataset2$bandit2arm[[65]],10)
# Visualize behavior
plot_bandit2arm(data = dataset2, subj = 65, colors = c("green","red"))

# Participant 33
# View first 10 rows of data
head(dataset2$bandit2arm[[33]],10)
# Visualize behavior
plot_bandit2arm(data = dataset2, subj = 33, colors = c("#AA4499","#44AA99"))

Estimation

# Run MLE
estimate_bandit2arm(data = dataset1, method = "mle", plot = TRUE)

# Run MAP
estimate_bandit2arm(data = dataset1, method = "map", plot = TRUE)

# Run MLE
estimate_bandit2arm(data = dataset1, method = "eml", plot = TRUE)