NickCH-K

causalgraphs

R code for causal graph animations

causalbook

Replication code and downloadable example data sets for The Effect

EconometricsSlides

This is the repository for the slides used in the Seattle University Econometrics course

causaldata

Packages of Example Data for The Effect

CausalitySlides

Slides for the Seattle University Causal Inference Class

DataCommSlides

Slides for Seattle University Course on Data Communications

Econometrics

A Swirl course for introductory econometrics

TheEffectAssignments

Homework assignments to go along with The Effect

vtable

An R package for creating Variable Documentation Files

pmdplyr

Panel Maneuvers in dplyr: An R package for cleaning and manipulating panel and hierarchical data

did

A Stata package that acts as a wrapper for Callaway and Sant'anna's R did package

DataWranglingWorkshopFiles

These are the files for the walk-through example at the end of the data wrangling workshop(s)

mlrtime

A Stata package for running machine learning analyses in R

DataVizChecklist

A brief checklist to go through before you're done with your data visualization, or as you're using it.

nicksshorts

An R package with some convenience functions for graphing and data cleaning

TheEffectStyle

Files and tips for modifying the msmbstyle Bookdown style to look like The Effect

ManyEconomists

This repository is a central website describing the 2022 Many Economists Project

modelsummary

Beautiful and customizable model summaries in R.

SomeThoughts

A place to keep some brief blog-style thoughts, and when I have enough of them, a place to be annoyed I didn't set up a proper blogging structure the first time around.

econometrics_data_exploration

econometrics_data_exploration

flexdashboard

Easy interactive dashboards for R

MagIVStata

A Stata package for running Magnified IV/SLATE estimation

repl_data

Downloadable files

Robyn

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for granular datasets with many independent variables and therefore especially suitable for digital and direct response advertisers with rich dataset.

r2especcurve

A specification curve builder for the R2E project

did-1

Difference in Differences with Multiple Periods and Variation in Treatment Timing

knitr

A general-purpose tool for dynamic report generation in R

LOST-STATS.github.io

Source code for the Library of Statistical Techniques

My_course_project

My_project