Package: injurytools 2.0.1

injurytools: A Toolkit for Sports Injury and Illness Data Analysis

Sports Injury Data analysis aims to identify and describe the magnitude of the injury problem, and to gain more insights (e.g. determine potential risk factors) by statistical modelling approaches. The 'injurytools' package provides standardized routines and utilities that simplify such analyses. It offers functions for data preparation, informative visualizations and descriptive and model-based analyses.

Authors:Lore Zumeta Olaskoaga [aut, cre], Dae-Jin Lee [ctb]

injurytools_2.0.1.tar.gz
injurytools_2.0.1.zip(r-4.7-any)injurytools_2.0.1.zip(r-4.6-any)injurytools_2.0.1.zip(r-4.5-any)
injurytools_2.0.1.tgz(r-4.6-any)injurytools_2.0.1.tgz(r-4.5-any)
injurytools_2.0.1.tar.gz(r-4.7-any)injurytools_2.0.1.tar.gz(r-4.6-any)
injurytools_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
injurytools/json (API)

# Install 'injurytools' in R:
install.packages('injurytools', repos = c('https://lzumeta.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lzumeta/injurytools/issues

Pkgdown/docs site:https://lzumeta.github.io

Datasets:

On CRAN:

Conda:

sportssports-injuries

6.29 score 7 stars 28 scripts 411 downloads 25 exports 55 dependencies

Last updated from:42524f4102. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK176
source / vignettesOK249
linux-releaseOK232
macos-releaseOK190
macos-oldrelOK225
windows-develOK127
windows-releaseOK112
windows-oldrelOK115
wasm-releaseOK142

Exports:calc_burdencalc_exposurecalc_incidencecalc_iqr_dayslostcalc_mean_dayslostcalc_median_dayslostcalc_ncasescalc_ndayslostcalc_prevalencecalc_summarycheck_injfollowupcut_injddate2seasonget_data_exposuresget_data_followupget_data_injuriesgg_photogg_prevalencegg_rankgg_riskmatrixis_injdprepare_allprepare_expprepare_injseason2year

Dependencies:backportscachemcheckmateclassclassIntclicpp11data.tableDBIdigestdplyre1071farverfastmapforcatsFormulaformula.toolsgenericsggplot2gluegtableisobandKernSmoothlabelinglifecyclelubridatemagrittrmemoisemetRoperator.toolspillarpkgconfigplyrproxypurrrR6RColorBrewerRcpprlangs2S7scalessfstringistringrtibbletidyrtidyselecttimechangeunitsutf8vctrsviridisLitewithrwk

Model Sports Injuries as Counts
Exploring the distribution of injuries | - Poisson (mixed) model | - Negative Binomial model | - Zero-inflated Poisson model | - Zero-inflated Negative Binomial model | Model comparison
Rendered frommodel-injury-data-i.Rmdusingknitr::rmarkdown

Last update: 2026-01-26
Started: 2023-09-25

Prepare Sports Injury Data
Starting point | 1) prepare and standardize injury and exposure data | 2) integrate both sources of data | The prepared data set, an injd object
Rendered fromprepare-injury-data.Rmdusingknitr::rmarkdown

Last update: 2026-01-25
Started: 2022-08-25

Estimate Measures of Injury Epidemiology
Measures of occurrence | Rates | Injury incidence rate | Injury burden rate | Prevalence | In practice | - calc_summary() | - calc_prevalence() | Further implementation | Notes | References
Rendered fromestimate-epi-measures.Rmdusingknitr::rmarkdown

Last update: 2024-06-11
Started: 2022-08-25

Model Sports Injuries as Events
Brief background | Methods for time to first injury | Kaplan-Meier curve | Cox PH model | Models for time to (subsequent) injuries | Stratified Cox PH model | Shared frailty model
Rendered frommodel-injury-data-ii.Rmdusingknitr::rmarkdown

Last update: 2024-06-11
Started: 2023-09-25

Visualize Sports Injury Data
A quick glance | Comparing injuries occurred in 17/18 vs. 18/19 | - Who were the most injured players? And the most severely affected? | - Which injuries were more frequent? And more burdensome? | - How many players were injured in each month?
Rendered fromvisualize-injury-data.Rmdusingknitr::rmarkdown

Last update: 2024-06-11
Started: 2023-01-24