Package: stremr
Title: Streamlined Estimation of Survival for Static, Dynamic and
        Stochastic Treatment and Monitoring Regimes
Version: 0.2
Authors@R: c(
    person("Oleg", "Sofrygin", role=c("aut", "cre"), email="oleg.sofrygin@gmail.com"),
    person(c("Mark", "J."), "van der Laan", role="aut", email="laan@berkeley.edu"),
    person("Romain", "Neugebauer", role="aut", email="Romain.S.Neugebauer@kp.org"))
Description: 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, including the ensemble-based 
    SuperLearner ('h2oEnsemble').
    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.
URL: https://github.com/osofr/stremr
BugReports: https://github.com/osofr/stremr/issues
SystemRequirements: pandoc (http://pandoc.org) for generating and
        exporting markdown reports to other formats.
Depends: R (>= 3.2.1)
Imports: assertthat, data.table, methods, R6, Rcpp, rmarkdown, pander,
        speedglm, stats, stringr, zoo
LinkingTo: Rcpp
Suggests: devtools, h2o, h2oEnsemble, knitr, magrittr, RUnit, foreach,
        doParallel
Additional_repositories: https://osofr.github.io/drat/
License: GPL (>= 2)
LazyData: true
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-10-02 18:01:09 UTC; olegsofrygin
Author: Oleg Sofrygin [aut, cre],
  Mark J. van der Laan [aut],
  Romain Neugebauer [aut]
Maintainer: Oleg Sofrygin <oleg.sofrygin@gmail.com>
Repository: CRAN
Date/Publication: 2016-10-03 08:17:49
Built: R 3.3.2; x86_64-w64-mingw32; 2016-11-25 03:28:17 UTC; windows
Archs: i386, x64
