• PARAFAC

  • Referenced in 24 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...
  • Causal Discovery

  • Referenced in 2 articles [sw35440]
  • knowledge, aimed at causal graph and causal mechanism modeling. The Cdt package implements ... direct dependencies (the skeleton of the causal graph) and the causal relationships between variables...
  • 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
  • MVGC

  • Referenced in 11 articles [sw14339]
  • causal inference is based on multiple equivalent representations of a VAR model by (i) regression...
  • TATES

  • Referenced in 3 articles [sw20044]
  • loss of statistical power to detect causal variants. Multivariate genotype-phenotype methods do exist ... probing a wide variety of genotype-phenotype 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 genotype-phenotype model is usually unknown and probably phenotypically...
  • doseresponse

  • Referenced in 2 articles [sw30475]
  • Hirano and Imbens (2004, Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives...
  • overlap

  • Referenced in 1 article [sw34699]
  • minimal modeling assumptions in order to preserve the ability to estimate population average causal effects ... framework to estimate population average causal effects with minor model dependence and appropriately large uncertainties ... causal effects in the overlap and non-overlap regions are delegated to two distinct models ... support means reliance on model specification is necessary, individual causal effects are estimated by extrapolating...
  • cplint

  • Referenced in 6 articles [sw22924]
  • perform causal reasoning. In particular, we consider Pearl’s do calculus for models where ... models. We also executed experiments comparing exact and approximate inference with conditional and causal queries...
  • nonlinearICP

  • Referenced in 1 article [sw36711]
  • package nonlinearICP: Invariant Causal Prediction for Nonlinear Models. Performs ’nonlinear Invariant Causal Prediction’ to estimate ... Peters and N. Meinshausen: ’Invariant Causal Prediction for Nonlinear Models...
  • 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...
  • CausalKinetiX

  • Referenced in 4 articles [sw37630]
  • existence of an underlying, invariant kinetic model, a key criterion for reproducible research. Results ... systems benefits from a causal perspective. The identified variables and models allow for a concise...
  • bpbounds

  • Referenced in 2 articles [sw37356]
  • bounds for the causal effect in a binary instrumental-variable model. Instrumental variables ... inferences about causal effects in the presence of unmeasured confounding. For a model in which ... intervention probabilities and the average causal effect. We have implemented these bounds in two commands...
  • cna

  • Referenced in 0 articles [sw19675]
  • package cna. Causal Modeling with Coincidence Analysis. Provides comprehensive functionalities for causal modeling with Coincidence...
  • CompareCausalNetworks

  • Referenced in 0 articles [sw17930]
  • bivariate additive noise model), ’bivariateCAM’ (bivariate causal additive model), ’CAM’ (causal additive model) (from package...
  • CausalMBSTS

  • Referenced in 1 article [sw41972]
  • package CausalMBSTS: MBSTS Models for Causal Inference and Forecasting. Infers the causal effect ... Multivariate Bayesian Structural Time Series models (MBSTS) as described in Menchetti & Bojinov (2020) . The package...
  • CP-logic

  • Referenced in 19 articles [sw06947]
  • formalization, a set of probabilistic causal laws can be used to represent a class ... probability distribution over the well-founded models of certain logic programs, rendering it formally quite ... contained way as a representation of probabilistic causal laws, this provides...
  • SAMTx

  • Referenced in 1 article [sw42796]
  • general bias formula and provides adjusted causal effect estimates in response to various assumptions about ... Model (BART) is used for outcome modeling. The causal estimands are the conditional average treatment...
  • ipw

  • Referenced in 5 articles [sw24292]
  • weights when estimating causal effects from observational data via marginal structural models. Both point treatment...
  • CausalGAM

  • Referenced in 2 articles [sw15401]
  • package CausalGAM: Estimation of Causal Effects with Generalized Additive Models. This package implements various estimators...