causal-analysis

Streamline a data analysis process. A book on data analysis, causal inference, and econometrics, written for readers with little to no prior background who want to develop both statistical intuition and practical R skills.

course on data science for economists

Spatial Empirical Dynamic Modeling

Temporal Empirical Dynamic Modeling

The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).

CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior

This repository is created to support the paper 'CAMS: An Annotated Corpus for Causal Analysis of Mental health on Social media' which is submitted to Language Resources and Evaluation Conference 2022 we introduce a new dataset for Causal Analysis of Mental health illness in Social media posts (CAMS). We first introduce the annotation schema for…

[ICML 2026] Probing Cross-modal Information Hubs in Audio-Visual LLMs

How much of your AI-written code actually survives? Find out in 10 seconds - one command, any git repo, zero setup. Then go deeper: a causal ledger that records every prompt, model and change an AI agent makes, so you can trace, diff and revert them like git commits.

CausalVerse: An R toolkit expediting causal research & analysis. Streamlines complex methodologies, empowering users to unveil causal relationships with precision. Your go-to for insightful causality exploration.

Full-featured Decision Trees and Random Forests learner.

Transmission Channel Analysis in Dynamic Models

Análise Causal Heterogênea para Subgrupos de Intervenção em Ansiedade

The repository shows an approach to perform casual inference on Breast Cancer Data. Causal inference is carried out to determine the independent, actual effect of breast cancer that is component of a larger system

WorldBisect: bounded causal diagnostics for Linux command/runtime failure analysis

Toolbox for Transmission Channel Analysis in Matlab

Code for investigating the factors affecting GRDP in a provincial level, and the short‑term, long‑term, and overall effects of the affecting variables.

Friendly introduction to causal inference

Analyzing global commodity shocks and trade linkages to predict sectoral stress and economic resilience in India.