suddengains: Identify Sudden Gains in Longitudinal Data (original) (raw)
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.
Version:
0.7.2
Depends:
R (≥ 3.5.0)
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)
Published:
2023-02-28
DOI:
10.32614/CRAN.package.suddengains
Author:
Milan Wiedemann [aut, cre], Graham M Thew
[aut], Richard Stott
[ctb], Anke Ehlers
[ctb, ths], Mental Health Research UK [fnd], Wellcome Trust [fnd]
Maintainer:
Milan Wiedemann <milan.wiedemann at gmail.com>
BugReports:
https://github.com/milanwiedemann/suddengains/issues
License:
MIT + file
URL:
https://milanwiedemann.github.io/suddengains/
NeedsCompilation:
no
Language:
en-US
Citation:
Materials:
CRAN checks: