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-4.5)visR_0.4.1.zip(r-4.4)visR_0.4.1.zip(r-4.3)
visR_0.4.1.tgz(r-4.4-any)visR_0.4.1.tgz(r-4.3-any)
visR_0.4.1.tar.gz(r-4.5-noble)visR_0.4.1.tar.gz(r-4.4-noble)
visR_0.4.1.tgz(r-4.4-emscripten)visR_0.4.1.tgz(r-4.3-emscripten)
visR.pdf |visR.html✨
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

Datasets:

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

On CRAN:

8.43 score 179 stars 98 scripts 112 downloads 31 exports 91 dependencies

Last updated 7 months agofrom:83198e4127. Checks:OK: 5 ERROR: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 11 2024
R-4.5-win	ERROR	Oct 11 2024
R-4.5-linux	ERROR	Oct 11 2024
R-4.4-win	OK	Oct 11 2024
R-4.4-mac	OK	Oct 11 2024
R-4.3-win	OK	Oct 11 2024
R-4.3-mac	OK	Oct 11 2024

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 cli cmprsk colorspace commonmark cowplot cpp11 crosstalk curl digest dplyr DT evaluate fansi farver fastmap fontawesome forcats fs generics ggplot2 glue gridExtra gt gtable gtsummary hardhat highr htmltools htmlwidgets httpuv isoband jquerylib jsonlite juicyjuice kableExtra knitr labeling later lattice lazyeval lifecycle magrittr markdown MASS Matrix memoise mgcv mime munsell nlme pillar pkgconfig promises purrr R6 rappdirs RColorBrewer Rcpp reactable reactR rlang rmarkdown rstudioapi sass scales stringi stringr survival svglite systemfonts tibble tidycmprsk tidyr tidyselect tinytex utf8 V8 vctrs viridisLite withr xfun xml2 yaml

Creating consort flow diagram with visR

Rendered fromConsort_flow_diagram.Rmdusingknitr::rmarkdownon Oct 11 2024.

Last update: 2022-06-22
Started: 2021-06-02

Styling survival plots

Rendered fromStyling_KM_plots.Rmdusingknitr::rmarkdownon Oct 11 2024.

Last update: 2022-06-22
Started: 2021-06-02

Survival Analysis with visR

Rendered fromTime_to_event_analysis.Rmdusingknitr::rmarkdownon Oct 11 2024.

Last update: 2022-06-22
Started: 2021-03-18

Survival Analysis with visR using CDISC ADaM Time-To-Event Analysis Dataset (ADTTE)

Rendered fromCDISC_ADaM.Rmdusingknitr::rmarkdownon Oct 11 2024.

Last update: 2022-06-22
Started: 2021-03-24

Citation

Development and contributors

Readme and manuals

Help Manual

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