DESCRIPTION

Package: suddengains
Title: Identify Sudden Gains in Longitudinal Data
Date: 2023-02-27
Version: 0.7.2
Authors@R: c(
  person("Milan", "Wiedemann", email = "milan.wiedemann@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1991-282X")),
  person("Graham M", "Thew", role = "aut", comment = c(ORCID = "0000-0003-2851-1315")),
  person("Richard", "Stott", role = "ctb", comment = c(ORCID = "0000-0003-2533-5504")),
  person("Anke", "Ehlers", role = c("ctb", "ths"), comment = c(ORCID = "0000-0002-8742-0192")),
  person("Mental Health Research UK", role = c("fnd")),
  person("Wellcome Trust", role = c("fnd"))
  )
Description: Identify sudden gains based on the three criteria outlined by Tang and DeRubeis (1999) <doi:10.1037/0022-006X.67.6.894> to a selection of repeated measures. Sudden losses, defined as the opposite of sudden gains can also be identified. Two different datasets can be created, one including all sudden gains/losses and one including one selected sudden gain/loss for each case. It can extract scores around sudden gains/losses. It can plot the average change around sudden gains/losses and trajectories of individual cases.
Depends: 
    R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://milanwiedemann.github.io/suddengains/
BugReports: https://github.com/milanwiedemann/suddengains/issues
LazyData: true
Imports:
    dplyr (>= 0.8.0),
    tibble (>= 2.1.1),
    magrittr (>= 1.5),
    rlang (>= 0.3.4),
    stringr (>= 1.4.0),
    ggplot2 (>= 3.1.1),
    psych (>= 1.8.12),
    readr (>= 1.3.1),
    tidyr (>= 0.8.2),
    ggrepel (>= 0.8.0),
    patchwork (>= 1.0.0),
    forcats,
    naniar,
    scales,
    cli
Suggests:
    haven (>= 2.1.0),
    writexl (>= 1.1.0),
    knitr (>= 1.21),
    DT (>= 0.5),
    rmarkdown (>= 1.11),
    spelling (>= 2.1)
RoxygenNote: 7.2.3
VignetteBuilder: knitr
Language: en-US