Christian Testa's repositories
intro_to_functional_programming_2023
A brief intro to functional programming in R covering the apply family and purrr::map
covid.gradient.estimation
Using generalized additive models to analyze COVID-19 US county level mortality data
tikz-examples
Examples of tikz figures
CausalFall2023
Notes on readings in Causal Inference, Fall 2023
ecosocial_theory_tikz
Practice with LaTeX's diagram package TikZ
ggtriangles
use geom_triangles in ggplot2 in R to plot triangles with a base at (x,y) and height z
PrincipalComponentAnalysis
An HTML handout on principal component analysis
shelling_model
R code to animate the Shelling model of segregation
spatial_poisson_covid
A sparse CAR Poisson model of US COVID-19 county deaths in June 2020 - February 2021
ctesta.com
My personal website and blog
longitudinal_eda_talk
A presentation on exploratory data visualization for longitudinal data in R using dplyr and ggplot2
BST234Algorithms
Notes for Data Structures and Algorithms
bst258_hw1
Homework 1 (Reading Review & Problem Set) for BST 258, Causal Inference Theory and Practice
bst258_hw2
Homework 2 for BST 258 at Harvard
characteristic_functions
Visualizations of characteristic functions (e.g., Fourier transforms of probability density functions)
cook_county_mortality_leaflet
A leaflet example for visualizing mortality in the Cook County COVID-19 mortality dataset
dummyConverters
Provides functions to convert categorical variables to dummy variables and vice-versa
EvolutionaryEpidemiologyEPI519
Notes from Evolutionary Epidemiology, EPI 519
lda_ngrams
A demonstration of n-gram analysis within Latent Dirichlet Allocation model-assigned clusters of text
MethodsBST232
Notes from Methods, BST 232
multiple_mediators
example mediation analysis code for working with multiple mediators
PrincipalStratification_slides
Slides on Principal Stratification in Causal Inference by Frangakis and Rubin (2002)
ProbBST230
Notes from Probability, BST 230 at Harvard
RPSLS
Rock Paper Scissors Lizard Spock in R
spearman_1904
Spearman's 1904 work on 'General Intelligence' launched the field of factor analysis into existence. This slide-deck discusses the details and aftermath.