Impact Measurement Toolkit

A toolkit for causal inference in experimental and observational studies. Implements various simple Bayesian models including linear, negative binomial, and logistic regression for impact estimation. Provides functionality for randomization and checking baseline equivalence in experimental designs. The package aims to simplify the process of impact measurement for researchers and analysts across different fields. Examples and detailed usage instructions are available at < https://book.martinez.fyi>.

imt

Within this package, you will find a collection of straightforward tools designed to assist in impact measurement. These tools include functions for randomization, checking baseline balance, and fitting basic Bayesian models, such as linear, logistic, and negative binomial models.

Installation

You can install the development version of imt from GitHub with:

# install.packages("pak")
pak::pak("google/imt")

Example

Examples for how to use the function included in this package can be found here