Package overview | How to use the package | Step 1: Data loading | Step 2: Data preparation | Step 3: Running integrity checks | Step 4: Reviewing results by integrity domain | Domain 1: Unusual or repeated data patterns | Domain 2: Baseline characteristics | Domain 3: Correlations | Domain 4: Date violations | Domain 5: Patterns of allocation | Domain 6: Internal inconsistencies | Domain 7: External inconsistencies | Domain 8: Plausibility of data | Computing Environment
Package: integrity 1.0.3
integrity: Assessing the Integrity and Trustworthiness of Clinical Trials Data
The integrity package implements the IPD Integrity Tool, a structured and transparent framework for evaluating the integrity of individual participant data (IPD) from randomised trials (see Hunter et al. (2024) <doi:10.1002/jrsm.1738> and <doi:10.1002/jrsm.1739>). It supports users to identify potential issues, such as unusual data patterns, implausible values, lack of expected correlations, date violations, and inconsistencies. The package provides reproducible workflows for screening, documenting and summarising integrity concerns, and may be applied by evidence synthesists, editors, and others to determine whether a randomised trial may be considered sufficiently trustworthy to contribute to the evidence base that informs policy and practice.
Authors:
integrity_1.0.3.tar.gz
integrity_1.0.3.zip(r-4.7-any)integrity_1.0.3.zip(r-4.6-any)integrity_1.0.3.zip(r-4.5-any)
integrity_1.0.3.tgz(r-4.6-any)integrity_1.0.3.tgz(r-4.5-any)
integrity_1.0.3.tar.gz(r-4.7-any)integrity_1.0.3.tar.gz(r-4.6-any)
integrity_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
integrity/json (API)
| # Install 'integrity' in R: |
| install.packages('integrity', repos = c('https://sollibesman.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:2e4d29f78a. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 169 | ||
| source / vignettes | OK | 513 | ||
| linux-release | OK | 146 | ||
| macos-release | OK | 141 | ||
| macos-oldrel | OK | 152 | ||
| windows-devel | OK | 113 | ||
| windows-release | OK | 113 | ||
| windows-oldrel | OK | 126 | ||
| wasm-release | OK | 131 |
Exports:read_metadata_excelread_metadata_rrun_checks
Dependencies:abindbackportsbase64encbigDbitopsbootbroombslibcachemcarcarDatacardscardxclicolorspacecommonmarkcorrplotcowplotcpp11curlDerivdigestdoBydplyrevaluatefarverfastmapfontawesomeforecastFormulafracdifffsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtgtablegtsummaryhighrhmshtmltoolshtmlwidgetsisobandjanitorjquerylibjsonlitejuicyjuiceknitrlabelinglatticelifecyclelitedownlme4lmtestlubridatemagrittrmarkdownMASSMatrixMatrixModelsmemoisemgcvmimeminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreactablereactRreformulasrlangrmarkdownrstatixS7sassscalessnakecaseSparseMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetinytexurcautf8V8vctrsviridisLitewithrxfunxml2yamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Check Variability Between Intervention and Control Groups | .differential_variability |
| Check Day of Week of Randomisation for Non-uniformity | .imbalance_day_intervention |
| Check Variables for Implausible Values | .implausible_values |
| Check clinical Data Matches its Data Specification | .prepare_data |
| Check Baseline Variables for Repetition | .repeating_baseline |
| Check Terminal Digits of Numerical Variables for Non-uniformity | .terminal_digits |
| Check Pairs of Variables Expected to be Correlated | .unexpectedly_uncorrelated |
| Read Dataset Metadata from an Excel Template | read_metadata_excel |
| Read Dataset Metadata from an R Script | read_metadata_r |
| Run a Suite of Integrity Checks Based on Dataset Annotation | run_checks |