JOSS Papers: Causal inference

Published Papers

published Published 29 days ago

jointVIP: Prioritizing variables in observational study design with joint variable importance plot in R

R

10.21105/joss.06093

published Published 9 months ago

GPCERF - An R package for implementing Gaussian processes for estimating causal exposure response curves

R C++

10.21105/joss.05465

published Published 9 months ago

konfound: An R Sensitivity Analysis Package to Quantify the Robustness of Causal Inferences

R

10.21105/joss.05779

published Published 12 months ago

CRE: An R package for interpretable discovery and inference of heterogeneous treatment effects

R

10.21105/joss.05587

published Published about 1 year ago

SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R

R

@blind-contours

10.21105/joss.05422

published Published over 1 year ago

tehtuner: An R package to fit and tune models for the conditional average treatment effect

R

10.21105/joss.05453

published Published almost 2 years ago

CVtreeMLE: Efficient Estimation of Mixed Exposures using Data Adaptive Decision Trees and Cross-Validated Targeted Maximum Likelihood Estimation in R

R

@blind-contours

10.21105/joss.04181

published Published about 2 years ago

haldensify: Highly adaptive lasso conditional density estimation in R

R

10.21105/joss.04522

published Published over 2 years ago

tipr: An R package for sensitivity analyses for unmeasured confounders

R

10.21105/joss.04495

published Published over 2 years ago

GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference

Python

10.21105/joss.04534

Displaying papers 1 - 10 of 16 in total

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