Nothing
bayesmsm: Fitting Bayesian Marginal Structural Models for Longitudinal Observational Data
Implements Bayesian marginal structural models for causal effect estimation with time-varying treatment and confounding. It includes an extension to handle informative right censoring. The Bayesian importance sampling weights are estimated using JAGS. See Saarela (2015) <doi:10.1111/biom.12269> for methodological details.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Kuan Liu [aut, cre, cph] (ORCID: <https://orcid.org/0000-0002-5017-1276>), Xiao Yan [aut] (ORCID: <https://orcid.org/0000-0001-9712-1199>), Martin Urner [aut] (ORCID: <https://orcid.org/0000-0003-1133-4885>) |
| Maintainer | Kuan Liu <kuan.liu@utoronto.ca> |
| License | MIT + file LICENSE |
| Version | 1.0.0 |
| URL | https://github.com/Kuan-Liu-Lab/bayesmsm |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the bayesmsm package in your browser
Any scripts or data that you put into this service are public.
