its2es: This package implements interrupted time series analysis for both continuous and count outcomes, and quantifies the associated effect size, as described in Effect size quantification for interrupted time series analysis: Implementation in R and analysis for Covid-19 research. The main functions fit an ITS regression model, and then use the fitted values and the model-based counterfactual values to quantify the effect size (Cohen’s d for continuous outcomes and relative risk for count outcomes).
KMforCSD: KMforCSD is an R package containing the algorithm and the simulated data examples from the paper Kernel Machines for Current Status Data. See also the MLR3 wrapper.
This repository contains the code for the simulations and data analysis from the paper "Pseudo-Observations for Bivariate Survival Data".