
TETRAD
 Referenced in 336 articles
[sw12177]
 predicts with, and searches for causal and statistical models. The aim of the program...

MIM
 Referenced in 107 articles
[sw26139]
 dependencies, both associational and causal, between the variables in the model. This textbook provides ... variables. Further chapters cover hypothesis testing and model selection. Chapters ... causal inference, relevant when graphical models are given a causal interpretation. This book will provide...

vars
 Referenced in 25 articles
[sw04507]
 package vars: VAR Modelling , Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance...

VipTool
 Referenced in 13 articles
[sw13755]
 project is to establish a simulation and modelling concept for business processes given by Petri ... bundle of methods concerned with causality and concurrency modelled by partially ordered runs of p/tnets...

causaleffect
 Referenced in 3 articles
[sw11067]
 Expressions of Joint Interventional Distributions in Causal Models. An implementation of the complete identification algorithm ... expressions of joint interventional distributions in causal models, which contain unobserved variables and induce directed...

MatchIt
 Referenced in 12 articles
[sw10538]
 MatchIt: Nonparametric Preprocessing for Parametric Causal Inference. MatchIt implements the suggestions of Ho, Imai, King ... Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching methods. MatchIt ... dependence of causal inferences on hardtojustify, but commonly made, statistical modeling assumptions...

DirectLiNGAM
 Referenced in 6 articles
[sw15504]
 Structural equation models and Bayesian networks have been widely used to analyze causal relations between ... structure of a linear acyclic model, that is, a causal ordering of variables and their ... direct method to estimate a causal ordering and connection strengths based on nonGaussianity ... steps if the data strictly follows the model, that is, if all the model assumptions...

dagitty
 Referenced in 3 articles
[sw16593]
 dagitty.net>, for analyzing structural causal models (also known as directed acyclic graphs or DAGs ... package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications ... separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation...

CAM
 Referenced in 2 articles
[sw23430]
 package CAM: Causal Additive Model (CAM) .The code takes an n x p data matrix ... fits a Causal Additive Model (CAM) for estimating the causal structure of the underlying process ... Bühlmann, J. Peters, J. Ernest: ”CAM: Causal Additive Models, highdimensional order search and penalized...

mediation
 Referenced in 12 articles
[sw04536]
 addition to the estimation of causal mediation effects, the software also allows researchers to conduct ... sensitivity analysis for certain parametric models...

SCTLMUS
 Referenced in 8 articles
[sw02245]
 order to formalise this model, a multivalued causal temporal logic, referred to as Simple ... Causal Temporal Logic (SCTL), is defined for the acquisition and specification of the functional requirements ... Model of Unspecified States (MUS) is also defined with a double goal: firstly, to show...

Horus
 Referenced in 15 articles
[sw21811]
 group communications model providing (among others) unreliable or reliable FIFO, causal, or total group multicasts...

semibart
 Referenced in 1 article
[sw31324]
 result is a Bayesian semiparametric linear regression model where the posterior distribution of the parameters ... example of this occurs in causal modeling with the structural mean model (SMM). Under certain...

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

TATES
 Referenced in 3 articles
[sw20044]
 loss of statistical power to detect causal variants. Multivariate genotypephenotype methods do exist ... probing a wide variety of genotypephenotype models, show that TATES’s false positive rate ... that TATES’s statistical power to detect causal variants explaining 0.5% of the variance ... complex traits. As the actual causal genotypephenotype model is usually unknown and probably phenotypically...

MVGC
 Referenced in 9 articles
[sw14339]
 causal inference is based on multiple equivalent representations of a VAR model by (i) regression...

PARAFAC
 Referenced in 19 articles
[sw14789]
 separate ‘rotation’ phase of analysis. The model can be used several ways ... factors found appear to correspond to the causal influences manipulated in the experiment, revealing their ... Several generalizations of the parallel factor analysis model are currently under development, including ones that...

TimeSquare
 Referenced in 4 articles
[sw15830]
 verification of causal and temporal constraints. It implements the MARTE Time Model and its specification...

PARAMED
 Referenced in 1 article
[sw23418]
 mediation analysis using parametric regression models. paramed performs causal mediation analysis using parametric regression models...

gma
 Referenced in 1 article
[sw26339]
 model for the time series of a single participant performs the causal mediation analysis ... which integrates the structural equation modeling and the Granger causality frameworks. A vector autoregressive model...