---
title: AOVT02
subtitle: ANCOVA with Single End Point and Customized Table
---
------------------------------------------------------------------------
{{< include ../../_utils/envir_hook.qmd >}}
```{r setup, echo = FALSE, warning = FALSE, message = FALSE}
library(tern)
library(dplyr)
adsl <- random.cdisc.data::cadsl
adqs <- random.cdisc.data::cadqs
# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
adsl <- df_explicit_na(adsl)
adqs <- df_explicit_na(adqs)
adqs_single <- adqs %>%
filter(
AVISIT == "WEEK 1 DAY 8",
PARAMCD == "FKSI-FWB"
) %>%
mutate(CHG = ifelse(BMEASIFL == "Y", CHG, NA))
```
```{r include = FALSE}
webr_code_labels <- c("setup")
```
{{< include ../../_utils/webr_no_include.qmd >}}
## Output
This example will focus on data from a single visit "WEEK 1 DAY 8" and a single endpoint "FKSI-FWB". Only evaluable populations will be analyzed.
:::: panel-tabset
## Standard Table
::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview
```{r variant1, test = list(result_v1 = "result")}
lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("ARMCD", ref_group = "ARM A") %>%
append_varlabels(adqs_single, "PARAM") %>%
summarize_ancova(
vars = "CHG",
variables = list(arm = "ARMCD", covariates = NULL),
conf_level = 0.95,
var_labels = "Unadjusted comparison",
.labels = c(lsmean = "Mean", lsmean_diff = "Difference in Means"),
table_names = "unadjusted"
) %>%
summarize_ancova(
vars = "CHG",
variables = list(arm = "ARMCD", covariates = c("BASE", "STRATA1")),
conf_level = 0.95,
var_labels = "Adjusted comparison (covariates BASE and STRATA1)",
table_names = "adjusted"
)
result <- build_table(
lyt = lyt,
df = adqs_single,
alt_counts_df = adsl
)
result
```
```{r include = FALSE}
webr_code_labels <- c("variant1")
```
{{< include ../../_utils/webr.qmd >}}
:::
## Data Setup
```{r setup}
#| code-fold: show
```
::::
{{< include ../../_utils/save_results.qmd >}}
## `teal` App
::: {.panel-tabset .nav-justified}
## {{< fa regular file-lines fa-sm fa-fw >}} Preview
```{r teal, opts.label = c("skip_if_testing", "app")}
library(teal.modules.clinical)
## Data reproducible code
data <- teal_data()
data <- within(data, {
ADSL <- random.cdisc.data::cadsl
ADQS <- random.cdisc.data::cadqs
# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
ADSL <- df_explicit_na(ADSL)
ADQS <- df_explicit_na(ADQS)
})
datanames <- c("ADSL", "ADQS")
names(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]
## Reusable Configuration For Modules
ADSL <- data[["ADSL"]]
ADQS <- data[["ADQS"]]
arm_ref_comp <- list(
ARM = list(
ref = "B: Placebo",
comp = c("A: Drug X", "C: Combination")
),
ACTARMCD = list(
ref = "ARM B",
comp = c("ARM A", "ARM C")
)
)
## Setup App
app <- init(
data = data,
modules = modules(
tm_t_ancova(
label = "ANCOVA table",
dataname = "ADQS",
avisit = choices_selected(
choices = value_choices(ADQS, "AVISIT"),
selected = "WEEK 1 DAY 8"
),
arm_var = choices_selected(
choices = variable_choices(ADSL, c("ARM", "ACTARMCD")),
selected = "ARM"
),
arm_ref_comp = arm_ref_comp,
aval_var = choices_selected(
choices = variable_choices(ADQS, c("CHG", "AVAL")),
selected = "CHG"
),
cov_var = choices_selected(
choices = variable_choices(ADQS, c("BASE", "STRATA1", "SEX")),
selected = "STRATA1"
),
paramcd = choices_selected(
choices = value_choices(ADQS, "PARAMCD", "PARAM"),
selected = "FKSI-FWB"
)
)
)
)
shinyApp(app$ui, app$server)
```
{{< include ../../_utils/shinylive.qmd >}}
:::
{{< include ../../repro.qmd >}}
