DESCRIPTION

Package: dsROCGLM
Type: Package
Title: ROC and calibration analysis for DataSHIELD
Authors@R:
    c(person(given = "Daniel",
        family = "Schalk",
        role = c("aut", "cre"),
        email = "daniel.schalk@stat.uni-muenchen.de"))
Version: 1.0.0
License: LGPL-3
Description: Methods to conduct distributed ROC and calibration analyses. The basis is the DataSHIELD
    (https://www.datashield.org) infrastructure for distributed computing. This
    package provides the calculation of the ROC-GLM (https://www.jstor.org/stable/2676973?seq=1) as well as
    AUC confidence intervals (https://www.jstor.org/stable/2531595?seq=1). To assess the calibration, methods
    to calculate the Brier score and calibration curves are part of the package. Last part of the package are
    methods to push models and predict models at the DataSHIELD server which is necessary for the analysis.
    DataSHIELD uses an option `datashield.privacyLevel` to indicate the minimal amount of numbers required to
    be allowed to share an aggregated value of these numbers. Instead of setting the option, we directly retrieve
    the privacy level from the DESCRIPTION (https://github.com/difuture-lmu/dsROCGLM/blob/master/DESCRIPTION)
    file each time a function calls for it. This options is set to 5 by default.
Depends:
    R (>= 3.1.0)
Imports:
    DSI,
    DSOpal,
    checkmate,
    stringr,
    digest,
    dsBaseClient
Suggests:
    ggplot2,
    testthat,
    opalr
Remotes:
    datashield/dsBaseClient
AggregateMethods:
    calculateDistrGLMParts,
    getNegativeScoresVar,
    getPositiveScoresVar,
    getNegativeScores,
    getPositiveScores,
    l2sens,
    getDataSHIELDInfo,
    brierScore,
    calibrationCurve,
    getFiles
AssignMethods:
    rocGLMFrame,
    decodeBinary,
    assignPredictModel,
    removeMissings
Options: datashield.privacyLevel=5
RoxygenNote: 7.2.3