Package: CohortMethod
Type: Package
Title: New-user cohort method with large scale propensity and outcome models
Version: 1.0.3
Date: 2015-03-13
Author: Martijn J. Schuemie [aut, cre],
  Marc A. Suchard [aut],
  Patrick B. Ryan [aut]
Maintainer: Martijn J. Schuemie <schuemie@ohdsi.org>
Description: CohortMethod is an R package for performing new-user cohort studies in an
  observational database in the OMOP Common Data Model. It extracts the necessary data
  from a database in OMOP Common Data Model format, and uses a large set of covariates
  for both the propensity and outcome model, including for example all drugs, diagnoses,
  procedures, as well as age, comorbidity indexes, etc. Large scale regularized regression
  is used to fit the propensity and outcome models. Functions are included for trimming,
  stratifying and matching on propensity scores, as well as diagnostic functions, such as
  propensity score distribution plots and plots showing covariate balance before and after
  matching and/or trimming. Supported outcome models are (conditional) logistic regression,
  (conditional) Poisson regression, and (stratified) Cox regression.
License: Apache License 2.0
VignetteBuilder: knitr
Depends:
    R (>= 3.1.0),
    bit,
    DatabaseConnector (>= 1.1.2),
    Cyclops (>= 1.0.0)
Imports:
    ggplot2,
    ff,
    ffbase,
    plyr,
    Rcpp (>= 0.11.2),
    RJDBC,
    SqlRender (>= 1.1.0),
    survival
Suggests:
    testthat,
    pROC,
    gnm,
    knitr,
    rmarkdown
LinkingTo: Rcpp
NeedsCompilation: yes