Nothing
## ----library, echo=TRUE, message=FALSE, warning=FALSE, results="hide"---------
library(teal.modules.general) # used to create the app
library(dplyr) # used to modify data sets
## ----data, echo=TRUE, message=FALSE, warning=FALSE, results="hide"------------
data <- teal_data()
data <- within(data, {
ADSL <- teal.data::rADSL %>%
mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
ADRS <- teal.data::rADRS
ADTTE <- teal.data::rADTTE
ADLB <- teal.data::rADLB %>%
mutate(CHGC = as.factor(case_when(
CHG < 1 ~ "N",
CHG > 1 ~ "P",
TRUE ~ "-"
)))
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
## ----app, echo=TRUE, message=FALSE, warning=FALSE, results="hide"-------------
# configuration for the single wide dataset
mod1 <- tm_a_regression(
label = "Single wide dataset",
response = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE
)
),
regressor = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
selected = "AGE",
multiple = TRUE,
fixed = FALSE
)
)
)
# configuration for the two wide datasets
mod2 <- tm_a_regression(
label = "Two wide datasets",
default_plot_type = 2,
response = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2")),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE
)
),
regressor = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
selected = c("AGE", "RACE"),
multiple = TRUE,
fixed = FALSE
)
)
)
# configuration for the same long datasets (same subset)
mod3 <- tm_a_regression(
label = "Same long datasets (same subset)",
default_plot_type = 2,
response = data_extract_spec(
dataname = "ADTTE",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADTTE"]], c("AVAL", "CNSR")),
selected = "AVAL",
multiple = FALSE,
fixed = FALSE
),
filter = filter_spec(
label = "Select parameter:",
vars = "PARAMCD",
choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
selected = "PFS",
multiple = FALSE
)
),
regressor = data_extract_spec(
dataname = "ADTTE",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADTTE"]], c("AGE", "CNSR", "SEX")),
selected = c("AGE", "CNSR", "SEX"),
multiple = TRUE
),
filter = filter_spec(
label = "Select parameter:",
vars = "PARAMCD",
choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
selected = "PFS",
multiple = FALSE
)
)
)
# configuration for the wide and long datasets
mod4 <- tm_a_regression(
label = "Wide and long datasets",
response = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[2],
multiple = TRUE,
label = "Select measurement:"
),
filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[2],
multiple = TRUE,
label = "Select visit:"
)
),
select = select_spec(
label = "Select variable:",
choices = "AVAL",
selected = "AVAL",
multiple = FALSE,
fixed = TRUE
)
),
regressor = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]], c("BMRKR1", "BMRKR2", "AGE")),
selected = "AGE",
multiple = TRUE,
fixed = FALSE
)
)
)
# configuration for the same long datasets (different subsets)
mod5 <- tm_a_regression(
label = "Same long datasets (different subsets)",
default_plot_type = 2,
response = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = TRUE,
label = "Select lab:"
),
filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = TRUE,
label = "Select visit:"
)
),
select = select_spec(
choices = "AVAL",
selected = "AVAL",
multiple = FALSE,
fixed = TRUE
)
),
regressor = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select labs:"
),
filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
),
select = select_spec(
choices = variable_choices(data[["ADLB"]], c("AVAL", "AGE", "BMRKR1", "BMRKR2", "SEX", "ARM")),
selected = c("AVAL", "BMRKR1"),
multiple = TRUE
)
)
)
# initialize the app
app <- init(
data = data,
modules = modules(
modules(
label = "Regression plots",
mod1,
mod2,
mod3,
mod4,
mod5
)
)
)
## ----shinyapp, eval=FALSE-----------------------------------------------------
# shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))
## ----shinylive_url, echo = FALSE, results = 'asis', eval = requireNamespace("roxy.shinylive", quietly = TRUE)----
code <- paste0(c(
knitr::knit_code$get("library"),
knitr::knit_code$get("data"),
knitr::knit_code$get("app"),
knitr::knit_code$get("shinyapp")
), collapse = "\n")
url <- roxy.shinylive::create_shinylive_url(code)
cat(sprintf("[Open in Shinylive](%s)\n\n", url))
## ----shinylive_iframe, echo = FALSE, out.width = '150%', out.extra = 'style = "position: relative; z-index:1"', eval = requireNamespace("roxy.shinylive", quietly = TRUE) && knitr::is_html_output() && identical(Sys.getenv("IN_PKGDOWN"), "true")----
# knitr::include_url(url, height = "800px")
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