Package: SPARRAfairness
Title: Analysis of Differential Behaviour of SPARRA Score Across
        Demographic Groups
Version: 0.1.0.0
Authors@R: 
  c(person(given = "Ioanna",
           family = "Thoma",
           role = c("aut"),
           email = "ithoma@ed.ac.uk",
           comment = c(ORCID = "0000-0001-6928-2198")),
    person(given = "Catalina",
           family = "Vallejos",
           role = c("ctb"),
           email = "catalina.vallejos@ed.ac.uk",
           comment = c(ORCID = "0000-0003-3638-1960")), 
    person(given = "Louis",
           family = "Aslett",
           role = c("ctb"),
           email = "louis.aslett@durham.ac.uk",
           comment = c(ORCID = "0000-0003-2211-233X")), 
    person(given = "Jill",
           family = "Ireland",
           role = c("ctb"),
           email = "jill.ireland@phs.scot",
           comment = c(ORCID = "0009-0009-5324-6630")),  
    person(given = "Simon",
           family = "Rogers",
           role = c("ctb"),
           email = "simon.rogers@nhs.scot",
           comment = c(ORCID = "0000-0003-3578-4477")),                                
    person(given = "James",
           family = "Liley",
           role = c("cre","aut"),
           email = "james.liley@durham.ac.uk",
           comment = c(ORCID = "0000-0002-0049-8238")))
Maintainer: James Liley <james.liley@durham.ac.uk>
Description: The SPARRA risk score (Scottish Patients At Risk of
        admission and Re-Admission) estimates yearly risk of emergency
        hospital admission using electronic health records on a monthly
        basis for most of the Scottish population. This package
        implements a suite of functions used to analyse the behaviour
        and performance of the score, focusing particularly on
        differential performance over demographically-defined groups.
        It includes useful utility functions to plot
        receiver-operator-characteristic, precision-recall and
        calibration curves, draw stock human figures, estimate
        counterfactual quantities without the need to re-compute risk
        scores, to simulate a semi-realistic dataset. Our manuscript
        can be found at: <doi:10.1371/journal.pdig.0000675>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), stats, graphics, grDevices, matrixStats, ranger
Imports: mvtnorm,cvAUC,ggplot2,ggrepel,patchwork,scales
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-01 09:36:55 UTC; root
Author: Ioanna Thoma [aut] (<https://orcid.org/0000-0001-6928-2198>),
        Catalina Vallejos [ctb]
        (<https://orcid.org/0000-0003-3638-1960>), Louis Aslett [ctb]
        (<https://orcid.org/0000-0003-2211-233X>), Jill Ireland [ctb]
        (<https://orcid.org/0009-0009-5324-6630>), Simon Rogers [ctb]
        (<https://orcid.org/0000-0003-3578-4477>), James Liley [cre,
        aut] (<https://orcid.org/0000-0002-0049-8238>)
Repository: https://jamesliley.r-universe.dev
Date/Publication: 2025-04-09 12:40:02 UTC
RemoteUrl: https://github.com/cran/SPARRAfairness
RemoteRef: HEAD
RemoteSha: c9bfaa8c38d3402831666768f5c053d79cb4fb6a