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Package: visR 0.4.1

Mark Baillie

visR: Clinical Graphs and Tables Adhering to Graphical Principles

To enable fit-for-purpose, reusable clinical and medical research focused visualizations and tables with sensible defaults and based on graphical principles as described in: "Vandemeulebroecke et al. (2018)" <doi:10.1002/pst.1912>, "Vandemeulebroecke et al. (2019)" <doi:10.1002/psp4.12455>, and "Morris et al. (2019)" <doi:10.1136/bmjopen-2019-030215>.

Authors:Mark Baillie [aut, cre, cph], Diego Saldana [aut], Charlotta Fruechtenicht [aut], Marc Vandemeulebroecke [aut], Thanos Siadimas [aut], Pawel Kawski [aut], Steven Haesendonckx [aut], James Black [aut], Pelagia Alexandra Papadopoulou [aut], Tim Treis [aut], Rebecca Albrecht [aut], Ardalan Mirshani [ctb], Daniel D. Sjoberg [aut]

visR_0.4.1.tar.gz
visR_0.4.1.zip(r-4.7)visR_0.4.1.zip(r-4.6)visR_0.4.1.zip(r-4.5)
visR_0.4.1.tgz(r-4.6-any)visR_0.4.1.tgz(r-4.5-any)
visR_0.4.1.tar.gz(r-4.7-any)visR_0.4.1.tar.gz(r-4.6-any)
visR_0.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
visR/json (API)
NEWS

# Install 'visR' in R:

install.packages('visR', repos = c('https://pharmaverse.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/openpharma/visr/issues

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

Datasets:

adtte - Adtte - CDISC ADaM compliant time to event data set
brca_cohort - Cancer survival data

On CRAN:

6.22 score 188 stars 92 scripts 26 downloads 31 exports 90 dependencies

Last updated from:83198e4127. Checks:8 ERROR, 1 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	ERROR	293
source / vignettes	ERROR	256
linux-release-x86_64	ERROR	263
macos-release-arm64	ERROR	201
macos-oldrel-arm64	ERROR	155
windows-devel	ERROR	191
windows-release	ERROR	197
windows-oldrel	ERROR	176
wasm-release	OK	153

Exports:%>%add_annotation add_CI add_CNSR add_highlight add_quantiles add_risktable align_plots apply_attrition apply_theme define_theme estimate_cuminc estimate_KM get_attrition get_COX_HR get_pvalue get_quantile get_risktable get_summary get_tableone render stat_stepribbon StatStepribbon summarize_long summarize_short Surv Surv_CNSR tableone the_lhs tidyme visr

Dependencies:backports base64enc bigD bitops broom bslib cachem cards cardx cli cmprsk commonmark cowplot cpp11 crosstalk curl digest dplyr DT evaluate farver fastmap fontawesome forcats fs generics ggplot2 glue gridExtra gt gtable gtsummary hardhat highr htmltools htmlwidgets isoband jquerylib jsonlite juicyjuice kableExtra knitr labeling later lattice lazyeval lifecycle litedown magrittr markdown Matrix memoise mime otel pillar pkgconfig promises purrr R6 rappdirs RColorBrewer Rcpp reactable reactR rlang rmarkdown rstudioapi S7 sass scales sparsevctrs stringi stringr survival svglite systemfonts textshaping tibble tidycmprsk tidyr tidyselect tinytex utf8 V8 vctrs viridisLite withr xfun xml2 yaml

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Help page	Topics
Add annotations to a visR object	add_annotation
Add confidence interval (CI) to visR object	add_CI add_CI.ggsurvfit add_CI.ggtidycuminc
Add censoring symbols to a visR object	add_CNSR add_CNSR.ggsurvfit add_CNSR.ggtidycuminc
Highlight a specific strata	add_highlight add_highlight.ggsurvfit
Add quantile indicators to visR plot	add_quantiles add_quantiles.ggsurvfit
Add risk tables to visR plots through an S3 method	add_risktable add_risktable.ggsurvfit add_risktable.ggtidycuminc
adtte - CDISC ADaM compliant time to event data set	adtte
Align multiple ggplot graphs, taking into account the legend	align_plots
Apply list of inclusion/exclusion criteria to a patient-level dataframe	apply_attrition
Applies a theme to a ggplot object.	apply_theme
Cancer survival data	brca_cohort
Provides a simple wrapper for themes	define_theme
Competing Events Cumulative Incidence	estimate_cuminc
Wrapper for Kaplan-Meier Time-to-Event analysis	estimate_KM
Generate cohort attrition table	get_attrition
Summarize Hazard Ratio from a survival object using S3 method	get_COX_HR get_COX_HR.survfit
Summarize the test for equality across strata from a survival object using S3 method	get_pvalue
Wrapper around quantile methods	get_quantile get_quantile.survfit
Obtain risk tables for tables and plots	get_risktable get_risktable.survfit get_risktable.tidycuminc
Summarize the descriptive statistics across strata from a survival object using S3 method	get_summary get_summary.survfit
Calculate summary statistics	get_tableone get_tableone.default
Translates options for legend into a list that can be passed to ggplot2	legendopts
Render a data.frame, risktable, or tableone object as a table	render
Step ribbon statistic	StatStepribbon stat_stepribbon
Calculate summary statistics from a vector	summarize_long summarize_long.default summarize_long.factor summarize_long.integer summarize_long.numeric
Create abbreviated variable summary for table1	summarize_short summarize_short.default summarize_short.factor summarize_short.integer summarize_short.numeric
Create a Survival Object from CDISC Data	Surv_CNSR
Display a summary Table (i.e. table one)	tableone
Find the "lhs" in the pipeline	the_lhs
Extended tidy cleaning of selected objects using S3 method	tidyme tidyme.default tidyme.survfit
Plot a supported S3 object	visr visr.attrition visr.default visr.survfit visr.tidycuminc

Package: visR 0.4.1

visR: Clinical Graphs and Tables Adhering to Graphical Principles

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