diff --git a/DESCRIPTION b/DESCRIPTION index 88cef23a..12a3314e 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Type: Package Package: visR Title: Clinical Graphs and Tables Adhering to Graphical Principles -Version: 0.2.0.9001 +Version: 0.2.0.9002 Authors@R: c( person(given = "Mark", family = "Baillie", diff --git a/NEWS.md b/NEWS.md index 56db238a..1d7fb3e5 100644 --- a/NEWS.md +++ b/NEWS.md @@ -13,6 +13,8 @@ * Improved documentation for `visr()` and other generic functions. (#301) +* The `README` page has been updated with additional examples. () + # visR 0.2.0 * Initial CRAN release. diff --git a/README.Rmd b/README.Rmd index 9f9fbdb2..276d2fcc 100644 --- a/README.Rmd +++ b/README.Rmd @@ -82,9 +82,11 @@ Install the *latest stable* version from [GitHub](https://github.com/) with: devtools::install_github("openpharma/visR", ref = "main") ``` -## Example +## Examples -This is a basic example to demonstrate how the API can be used to add layers to a visualization. In this example a time to event analysis. The example calculates stratified Kaplan-Meier by treatment and then plots. Additional functions can be used to add uncertainty intervals, censoring information and a risk table. +#### Visualization + +This is a basic example to demonstrate how the API can be used to add layers to a visualization. This example demonstrates a time-to-event analysis. The example calculates and then plots stratified Kaplan-Meier by treatment. It is possible to add uncertainty intervals, censoring information, and a risk table using additional functions. ```{r example, warning=FALSE, message = FALSE} library(visR) @@ -103,6 +105,25 @@ adtte %>% ) ``` + +#### Summary Table + +The `tableone()` function presents summary statistics in a table format. + +```{r table, warning=FALSE, message = FALSE} +## table by treatment - without overall and render with GT +adtte %>% + dplyr::select(AGE, SEX, TRTA) %>% + visR::tableone( + strata = "TRTA", + overall = TRUE, + title = "Cohort Summary", + datasource = "ADaM Interim Dataset for Time-to-Event Analysis", + engine = "gt" + ) +``` + + ## Cite visR ```{text, comment="", eval = FALSE} @@ -117,4 +138,4 @@ Thank you to all contributors: ```{r warning=FALSE, echo=FALSE, message=FALSE} contr <- usethis::use_tidy_thanks("https://github.com/openpharma/visR") ``` -`r unique(c(paste((paste0("[@",contr,"](https://github.com/", contr, ")")), collapse = ", "), "[@cschaerfe ](https://github.com/cschaerfe)", "[@AlexandraP-21 ](https://github.com/AlexandraP-21)"))` \ No newline at end of file +`r unique(c(paste((paste0("[@",contr,"](https://github.com/", contr, ")")), collapse = ", "), "[@cschaerfe ](https://github.com/cschaerfe)", "[@AlexandraP-21 ](https://github.com/AlexandraP-21)"))` diff --git a/README.md b/README.md index 7bd9b63b..0d9cba27 100644 --- a/README.md +++ b/README.md @@ -70,13 +70,15 @@ with: devtools::install_github("openpharma/visR", ref = "main") ``` -## Example +## Examples + +#### Visualization This is a basic example to demonstrate how the API can be used to add -layers to a visualization. In this example a time to event analysis. The -example calculates stratified Kaplan-Meier by treatment and then plots. -Additional functions can be used to add uncertainty intervals, censoring -information and a risk table. +layers to a visualization. This example demonstrates a time-to-event +analysis. The example calculates and then plots stratified Kaplan-Meier +by treatment. It is possible to add uncertainty intervals, censoring +information, and a risk table using additional functions. ``` r library(visR) @@ -97,6 +99,519 @@ adtte %>% +#### Summary Table + +The `tableone()` function presents summary statistics in a table format. + +``` r +## table by treatment - without overall and render with GT +adtte %>% + dplyr::select(AGE, SEX, TRTA) %>% + visR::tableone( + strata = "TRTA", + overall = TRUE, + title = "Cohort Summary", + datasource = "ADaM Interim Dataset for Time-to-Event Analysis", + engine = "gt" + ) +``` + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Cohort Summary
Total (N=254)Placebo (N=86)Xanomeline High Dose (N=84)Xanomeline Low Dose (N=84)
AGE
Mean (SD)75.1 (8.25)75.2 (8.59)74.4 (7.89)75.7 (8.29)
Median (IQR)77 (70-81)76 (69.2-81.8)76 (70.8-80)77.5 (71-82)
Min-max51-8952-8956-8851-88
Missing0 (0%)0 (0%)0 (0%)0 (0%)
SEX
F143 (56.3%)53 (61.6%)40 (47.6%)50 (59.5%)
M111 (43.7%)33 (38.4%)44 (52.4%)34 (40.5%)
TRTA
Placebo86 (33.9%)NANANA
Xanomeline High Dose84 (33.1%)NANANA
Xanomeline Low Dose84 (33.1%)NANANA
Data Source: ADaM Interim Dataset for Time-to-Event Analysis
+
+ ## Cite visR ``` text diff --git a/man/figures/README-example-1.png b/man/figures/README-example-1.png index 347fd9e8..8692a4d6 100644 Binary files a/man/figures/README-example-1.png and b/man/figures/README-example-1.png differ