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:
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Generate Tables and visualizations for Regulatory Submission easily in R. Perfect for presenting descriptive statistics, statistical analyses, regressions, etc. and more.
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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.
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")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, error
Note 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.
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