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README.md

simMSM

Maintainer: Ehsan Karim

I am a big fan of scientific collaboration. Feel free to contact me to discuss your causal inference related projects for potential collaboration.

R package to generate data suitable for Marginal Structural Cox Model fit

  • This package simulates survival data suitable for fitting Marginal Structural Model.

Installation

library(devtools)
install_github("ehsanx/simMSM")

Loading the package

require(simMSM)

Pulling the help file

?simmsm

Setting working directory to save the generated datafiles

setwd("C:/data") # change working dir

Using this package to generate data in the working directory

simmsm(subjects = 2500, tpoints = 10, psi = 0.3, n = 1000)
# This code generates 1000 datasets (takes time!)
# 2500 subjects in each datasets
# Each subject followed upto 10 time-points (say, months)
# Causal effect (log-odds) is 0.3
Parameter Description
subjects Number of Subjects in each simulated dataset
tpoints Maximum number of time-points each subjects are followed
psi Causal effect parameter for Marginal Structural Model
n Number of simulated datasets an user wants to generate

Author

  • Ehsan Karim :octocat: (only R porting from the SAS code). I wrote them in R basically to understand the mechanism, but the SAS / SAS IML / Stata codes (I have them as well, available upon request) are faster than this. Feel free to report any errors / update suggestions.

Original Papers

Follow-up References

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R package that simulates data suitable for fitting Marginal Structural Model.

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