116 skills found · Page 1 of 4
CausalInference / GfoRmulaThe gfoRmula package implements the parametric g-formula in R. The parametric g-formula (Robins, 1986) uses longitudinal data with time-varying treatments and confounders to estimate the risk or mean of an outcome under hypothetical treatment strategies specified by the user.
PMBio / ScLVMscLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation.
rickystewart / ShittydbA confoundingly fast key-value store
kathoffman / Steroids Trial EmulationTutorial for a target trial emulation with a time-varying exposure, time-dependent confounding, time-to-event outcome, and Sequentially Doubly Robust estimation (Hoffman et al. 2022).
rpryzant / Deconfounded Lexicon InductionFind text features that are most related to an outcome, controlling for confounds.
vveitch / Causal Network EmbeddingsSoftware and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"
epigen / Spilterlize IntegrateA Snakemake workflow and MrBiomics module to split, filter, normalize, integrate and select highly variable features of count matrices resulting from next-generation sequencing (NGS) experiments (e.g., RNA-seq, ATAC-seq, ChIP-seq, Methyl-seq, miRNA-seq,...) including confounding factor analysis and diagnostic visualizations.
ioanabica / Time Series DeconfounderCode for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. Bica, A. M. Alaa, M. van der Schaar
RobinDenz1 / AdjustedCurvesAn R-Package to estimate and plot confounder-adjusted survival curves (single event survival data) and confounder-adjusted cumulative incidence functions (data with competing risks) using various methods.
darya-chyzhyk / Confound PredictionConfound-isolating cross-validation approach to control for a confounding effect in a predictive model.
r-causal / TiprAn R package for conducting sensitivity analyses for unmeasured confounders
raamana / ConfoundsConquering confounds and covariates: methods, library and guidance
SIMEXP / Load ConfoundsLoad fMRIprep confounds in python
CausalInference / GFORMULA SASThe GFORMULA macro implements the parametric g-formula in SAS. The parametric g-formula (Robins, 1986) uses longitudinal data with time-varying treatments and confounders to estimate the risk or mean of an outcome under hypothetical treatment strategies specified by the user.
wxwx1993 / GPSmatchingR Package for "Matching on generalized propensity scores with continuous exposures". An innovative approach for estimating causal effects using observational data in settings with continuous exposures, and a new framework for GPS caliper matching that jointly matches on both the estimated GPS and exposure levels to fully adjust for confounding bias.
CausalInference / PygformulaThe pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-varying treatments and confounders to estimate the risk or mean of an outcome under hypothetical treatment strategies specified by the user.
YueYANG1996 / KnoBoNeurIPS 2024 (spotlight): A Textbook Remedy for Domain Shifts Knowledge Priors for Medical Image Analysis
anishazaveri / Austen PlotsDemo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".
dcgerard / VicarVarious Ideas for Confounder Adjustment in Regression
anndvision / QuinceCode for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
