Stars
In this project I created python scripts and functions to simulate n of 1 studies based on given parameters
This R package provides basic functions to analyse n of 1 studies.
Effect modification and collapsibility when estimating the effectiveness of public health interventions: A Monte Carlo Simulation
regression-based estimation of heterogeneous treatment effects when extending inferences from a randomized trial to a target population
🦄 Scientific journal and sci-fi themed color palettes for ggplot2
Graphical displays for subgroup analysis in clinical trials
An R implementation of the UpSet set visualization technique published by Lex, Gehlenborg, et al..
RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
connector: A package for interacting with clinical data sets in the simple way
Simulating Longitudinal and Network Data with Causal Inference Applications
Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference
Estimation of Individual Treatment Effects with Machine Learning methods.
Uses Stan sampler and math library to semiparametrically fit linear and multilevel models with additive Bayesian Additive Regression Tree (BART) components.
Colorblind-friendly, qualitative Okabe-Ito Scales for ggplot2 and ggraph
A library for creating complex UpSet plots with ggplot2 geoms
Doubly Robust Machine Learner with sample splitting for Heterogeneous Treatment Effect Estimation and Approximately Optimal Treatments using Best Linear Projections
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
Implementation of TabTransformer, attention network for tabular data, in Pytorch
A curated list of causal inference libraries, resources, and applications.
A high-performance R 📦 for supervised and unsupervised machine learning evaluation metrics witten in 'C++'.