• MIM

  • Referenced in 129 articles [sw26139]
  • summarizes some recent work on causal inference, relevant when graphical models are given a causal...
  • pcalg

  • Referenced in 85 articles [sw06072]
  • package pcalg: Estimation of CPDAG/PAG and causal inference using the IDA algorithm , Standard and robust ... available for estimating PAGs. Functions for causal inference using the IDA algorithm (based...
  • MatchIt

  • Referenced in 13 articles [sw10538]
  • MatchIt: Nonparametric Preprocessing for Parametric Causal Inference. MatchIt implements the suggestions of Ho, Imai, King ... greatly reduce the dependence of causal inferences on hard-to-justify, but commonly made, statistical...
  • MVGC

  • Referenced in 10 articles [sw14339]
  • toolbox: A new approach to Granger-causal inference. The MVGC Matlab© Toolbox approach ... causal inference is based on multiple equivalent representations of a VAR model by (i) regression...
  • sbw

  • Referenced in 11 articles [sw21948]
  • probability weighting, are widely used for causal inference and estimation with incomplete outcome data. Part...
  • cplint

  • Referenced in 4 articles [sw22924]
  • Causal inference in cplint. cplint is a suite of programs for reasoning and learning with ... have extended cplint to perform causal reasoning. In particular, we consider Pearl’s do calculus ... measured. The two cplint modules for inference, PITA and MCINTYRE, have been extended for computing ... conditional and causal queries, showing that causal inference is often cheaper than conditional inference...
  • Surrogate

  • Referenced in 6 articles [sw16061]
  • meta-analytic, information-theoretic, and causal-inference frameworks. Part of this software has been developed...
  • simcausal

  • Referenced in 4 articles [sw25111]
  • package simcausal: Simulating Longitudinal Data with Causal Inference Applications. A flexible tool for simulating complex ... equations, with emphasis on problems in causal inference. Specify interventions and simulate from intervened data...
  • cvDSA

  • Referenced in 4 articles [sw06346]
  • cvDSA package groups several routines for causal inference with point treatment data based on Marginal...
  • JCI

  • Referenced in 2 articles [sw35495]
  • Joint causal inference from multiple contexts. The gold standard for discovering causal relations ... methods have been proposed that can infer causal relations between variables from certain statistical patterns ... purely observational data. We introduce Joint Causal Inference (JCI), a novel approach to causal discovery...
  • FLAME

  • Referenced in 2 articles [sw36879]
  • scale Almost Matching Exactly Approach to Causal Inference. A classical problem in causal inference...
  • CausalML

  • Referenced in 2 articles [sw32089]
  • Python implementation of algorithms related to causal inference and machine learning. Algorithms combining causal inference...
  • qtlnet

  • Referenced in 2 articles [sw23429]
  • package qtlnet: Causal Inference of QTL Networks. Functions to Simultaneously Infer Causal Graphs and Genetic...
  • rdmulti

  • Referenced in 3 articles [sw37337]
  • popular quasi-experimental design for causal inference and policy evaluation. The ’rdmulti’ package provides tools...
  • DoWhy

  • Referenced in 1 article [sw36878]
  • DoWhy: A Python package for causal inference. DoWhy is a Python library for causal inference ... based on a unified language for causal inference, combining causal graphical models and potential outcomes...
  • tmlenet

  • Referenced in 1 article [sw33571]
  • package: M. J. van der Laan, “Causal inference for a population of causally connected units ... Causal Inference J. Causal Infer...
  • D2C

  • Referenced in 2 articles [sw14323]
  • heart of all statistical approaches to causal inference. The D2C package implements a supervised machine ... learning approach to infer the existence of a directed causal link between two variables...
  • inferference

  • Referenced in 2 articles [sw23432]
  • package inferference: Methods for Causal Inference with Interference. Provides methods for estimating causal effects...
  • wfe

  • Referenced in 1 article [sw23425]
  • Linear Fixed Effects Regression Models for Causal Inference. Provides a computationally efficient way of fitting ... weighted linear fixed effects estimators for causal inference with various weighting schemes. Weighted linear fixed ... Linear Fixed Effects Regression Models for Causal Inference with Longitudinal Data?”, available at
  • CausalNLP

  • Referenced in 1 article [sw39095]
  • CausalNLP: A Practical Toolkit for Causal Inference with Text. The vast majority of existing methods ... systems for causal inference assume that all variables under consideration are categorical or numerical ... present CausalNLP, a toolkit for inferring causality from observational data that includes text in addition...