The {cardx} package is an extension of the {cards} package, providing additional functions to create Analysis Results Data Objects (ARDs) using the R programming language. The {cardx} package exports ARD functions that uses utility functions from {cards} and statistical functions from additional packages (such as, {stats}, {mmrm}, {emmeans}, {car}, {survey}, etc.) to construct summary objects.
Summary objects can be used to:
Generate Tables and visualizations for Regulatory Submission easily in R. Perfect for presenting descriptive statistics, statistical analyses, regressions, etc. and more.
Conduct Quality Control checks on existing Tables in R. Storing both the results and test parameters supports the re-use and verification of data analyses.
Installation
Install cards from CRAN with:
install.packages("cardx")You can install the development version of cards from GitHub with:
# install.packages("devtools")
devtools::install_github("insightsengineering/cardx")Examples
Example ARD Creation
Example t-test:
library(cardx)
cards::ADSL |>
# keep two treatment arms for the t-test calculation
dplyr::filter(ARM %in% c("Placebo", "Xanomeline High Dose")) |>
cardx::ard_stats_t_test(by = ARM, variable = AGE)## {cards} data frame: 14 x 9
## group1 variable context stat_name stat_label stat
## 1 ARM AGE stats_t_… estimate Mean Dif… 0.828
## 2 ARM AGE stats_t_… estimate1 Group 1 … 75.209
## 3 ARM AGE stats_t_… estimate2 Group 2 … 74.381
## 4 ARM AGE stats_t_… statistic t Statis… 0.655
## 5 ARM AGE stats_t_… p.value p-value 0.513
## 6 ARM AGE stats_t_… parameter Degrees … 167.362
## 7 ARM AGE stats_t_… conf.low CI Lower… -1.668
## 8 ARM AGE stats_t_… conf.high CI Upper… 3.324
## 9 ARM AGE stats_t_… method method Welch Tw…
## 10 ARM AGE stats_t_… alternative alternat… two.sided
## 11 ARM AGE stats_t_… mu H0 Mean 0
## 12 ARM AGE stats_t_… paired Paired t… FALSE
## 13 ARM AGE stats_t_… var.equal Equal Va… FALSE
## 14 ARM AGE stats_t_… conf.level CI Confi… 0.95
## ℹ 3 more variables: fmt_fn, warning, errorNote that the returned ARD contains the analysis results in addition to the function parameters used to calculate the results allowing for reproducible future analyses and further customization.
Model Input
Some {cardx} functions accept regression model objects as input:
lm(AGE ~ ARM, data = cards::ADSL) |>
ard_aod_wald_test()Note that the Analysis Results Standard should begin with a data set rather than a model object. To accomplish this we include model construction helpers.
construct_model(
data = cards::ADSL,
formula = reformulate2("ARM", response = "AGE"),
method = "lm"
) |>
ard_aod_wald_test()## {cards} data frame: 6 x 8
## variable context stat_name stat_label stat fmt_fn
## 1 (Intercept) aod_wald… df Degrees … 1 1
## 2 (Intercept) aod_wald… statistic Statistic 7126.713 1
## 3 (Intercept) aod_wald… p.value p-value 0 1
## 4 ARM aod_wald… df Degrees … 2 1
## 5 ARM aod_wald… statistic Statistic 1.046 1
## 6 ARM aod_wald… p.value p-value 0.593 1
## ℹ 2 more variables: warning, error