Analysis of longitudinal time-to-event or time-to-failure data. Estimates the counterfactual discrete survival curve under static, dynamic and stochastic interventions on treatment (exposure) and monitoring events over time. Estimators (IPW, MSM-IPW, GCOMP, longitudinal TMLE) adjust for measured time-varying confounding and informative right-censoring. Model fitting can be performed either with GLM or H2O-3 machine learning libraries. The exposure, monitoring and censoring variables can be coded as either binary, categorical or continuous. Each can be multivariate (e.g., can use more than one column of dummy indicators for different censoring events). The input data needs to be in long format.

Documentation

Manual: stremr.pdf
Vignette: None available.

Maintainer: Oleg Sofrygin <oleg.sofrygin at gmail.com>

Author(s): Oleg Sofrygin*, Mark J. van der Laan*, Romain Neugebauer*

Install package and any missing dependencies by running this line in your R console:

install.packages("stremr")

Depends R (>= 3.2.1)
Imports assertthat, data.table, methods, R6, Rcpp, rmarkdown, pander, speedglm, stats, stringr, zoo
Suggests devtools, h2o, knitr, magrittr, RUnit, foreach, doParallel
Enhances
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Package stremr
Materials
URL https://github.com/osofr/stremr
Task Views
Version 0.4
Published 2017-01-06
License GPL (>= 2)
BugReports https://github.com/osofr/stremr/issues
SystemRequirements pandoc (http://pandoc.org) for generating and exporting markdown reports to other formats.
NeedsCompilation yes
Citation
CRAN checks stremr check results
Package source stremr_0.4.tar.gz