DESCRIPTION

Package: CohortMethod
Type: Package
Title: New-user cohort method with large scale propensity and outcome models
Version: 2.0.4
Date: 2015-08-08
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 (>= 3.2.2),
    DatabaseConnector (>= 1.3.0),
    Cyclops (>= 1.2.0),
    FeatureExtraction  (>= 1.0.0)
Imports:
    bit,
    ggplot2,
    ff,
    ffbase (>= 0.12.1),
    plyr,
    Rcpp (>= 0.11.2),
    RJDBC,
    SqlRender (>= 1.1.1),
    survival,
    stringi
Suggests:
    testthat,
    pROC,
    gnm,
    knitr,
    rmarkdown,
    EmpiricalCalibration,
    OhdsiRTools (>= 1.1.1)
LinkingTo: Rcpp
NeedsCompilation: yes
RoxygenNote: 5.0.1