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teal
application to use cross table with various
datasets typesThis vignette will guide you through the four parts to create a
teal
application using various types of datasets using the
cross table module tm_t_crosstable()
:
app
variableInside this app 2 datasets will be used
ADSL
A wide data set with subject dataADLB
A long data set with lab measurements for each
subjectapp
variableThis is the most important section. We will use the
teal::init()
function to create an app. The data will be
handed over using teal.data::teal_data()
. The app itself
will be constructed by multiple calls of tm_t_crosstable()
using different combinations of data sets.
# configuration for the single wide dataset
mod1 <- tm_t_crosstable(
label = "Single wide dataset",
x = data_extract_spec(
"ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]]),
selected = names(data[["ADSL"]])[5],
multiple = TRUE,
fixed = FALSE,
ordered = TRUE
)
),
y = data_extract_spec(
"ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]]),
selected = names(data[["ADSL"]])[6],
multiple = FALSE,
fixed = FALSE
)
)
)
# configuration for the same long datasets (different subsets)
mod2 <- tm_t_crosstable(
label = "Same long datasets (different subsets)",
x = data_extract_spec(
dataname = "ADLB",
filter = filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE
),
select = select_spec(
choices = variable_choices(data[["ADLB"]]),
selected = "AVISIT",
multiple = TRUE,
fixed = FALSE,
ordered = TRUE,
label = "Select variable:"
)
),
y = data_extract_spec(
dataname = "ADLB",
filter = filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE
),
select = select_spec(
choices = variable_choices(data[["ADLB"]]),
selected = "LOQFL",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
)
)
# initialize the app
app <- init(
data = data,
modules = modules(
modules(
label = "Cross table",
mod1,
mod2
)
)
)
A simple shiny::shinyApp()
call will let you run the
app. Note that app is only displayed when running this code inside an
R
session.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.