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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.
Health stats visible at Monitor.