CRAN/E | suddengains

suddengains

Identify Sudden Gains in Longitudinal Data

Installation

About

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.

Citation suddengains citation info
milanwiedemann.github.io/suddengains/
Bug report File report

Key Metrics

Version 0.6.1
R ≥ 3.5.0
Published 2023-02-01 457 days ago
Needs compilation? no
License MIT
License File
CRAN checks suddengains results
Language en-US

Downloads

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Maintainer

Maintainer

Milan Wiedemann

milan.wiedemann@gmail.com

Authors

Milan Wiedemann

aut / cre

Graham M Thew

aut

Richard Stott

ctb

Anke Ehlers

ctb / ths

Mental Health Research UK

fnd

Wellcome Trust

fnd

Material

README
NEWS
Reference manual
Package source

Vignettes

shinygains: An interactive illustration of the suddengains R package
A tutorial on using the suddengains R package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

suddengains archive

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