Pinned Repositories
CAUSALab_Papers
Software used for papers published by CAUSALab members
CompetingEvents_Young_SIM_2020
R Code used in https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8471
gfoRmula
The 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.
gfoRmula-benchmark
Code and data used in the benchmark in "gfoRmula: An R package for estimating the effects of sustained treatment strategies via the parametric g-formula"
GFORMULA-RCT-SAS
GFORMULA-SAS
The 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.
IV-Bounds
MSM-SAS
pygformula
The 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.
Simulation-Scenarios-JAMA
code for article in JAMA
CAUSALab's Repositories
CausalInference/gfoRmula
The 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.
CausalInference/GFORMULA-SAS
The 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.
CausalInference/pygformula
The 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.
CausalInference/CAUSALab_Papers
Software used for papers published by CAUSALab members
CausalInference/CompetingEvents_Young_SIM_2020
R Code used in https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8471
CausalInference/Simulation-Scenarios-JAMA
code for article in JAMA
CausalInference/gfoRmula-benchmark
Code and data used in the benchmark in "gfoRmula: An R package for estimating the effects of sustained treatment strategies via the parametric g-formula"
CausalInference/IV-Bounds
CausalInference/MSM-SAS
CausalInference/GFORMULA-RCT-SAS
CausalInference/bariatric
Analytic code for bariatric analysis including synthetic data
CausalInference/pytruncreg
Estimation of Gaussian Truncated Regression Models
CausalInference/Resource_Constrained_dynMSM_Simulation
CausalInference/volume-patient
Paper and code for volume-outcomes analysis among patients undergoing pancreatectomy
CausalInference/Case_Crossover_Simulations
CausalInference/CausalCaseControl
CausalInference/NullParadox