The function optimall_shiny(), located within the
package optimall, launches a Shiny app that allows users to
observe how the stratum sizes, standard deviations, and optimum
allocations react to different stratum splits. This vignette
demonstrates how to use the application.
The first step in using optimall_shiny() is uploading
data. The data must be in the same format that the rest of
optimall’s functions require, meaning that each row must
corresponds to one sampling unit. If you have already updated an
existing dataset in your R workflow, you will have to save the updated
dataframe to a .csv file in order to work with it in
optimall_shiny().
Once the dataset has been uploaded, options for the user to select
inputs will appear. Each input correspond to an argument of at least one
function in optimall, and the application provides a list
of valid options for each one based on the uploaded data. See them
below:
Column Holding Strata corresponds to the
strata argument in split_strata(). The
dropdown menu includes a list of column names from which the user should
choose the name of the column that defines the stratum that each unit
belongs to.
Column Holding Variable to Split On corresponds
to the split_var argument in split_strata().
The dropdown menu includes a list of column names from which the user
should choose the name of the column that holds the variable (continuous
or categorical) that will be used to split strata on.
Column Holding Variable of Interest corresponds
to the y argument in optimum_allocation() or
allocate_wave(). The dropdown menu again includes a list of
column names from which the user should choose the column holding the
variable of interest. Since the application displays, it needs to know
this variable of interest, y, in order to calculate the
optimum allocation.
Name of Strata to Split corresponds to the
split argument in split_strata(). The dropdown
menu includes a list of the unique stratum names from the column holding
strata. Although the package allows for multiple strata to be selected
in the same call, the Shiny application currently supports only one (or
all) strata to be split at once.
Split Type corresponds to the
split_type argument in split_strata(). If the
variable to split on is not numeric, the type must be categorical. For
more details on each option, see the documentation at
?split_strata.
Split At corresponds to the
split_at argument in split_strata(). If the
split type is one of global quantile, local quantile, or value, this
input will be a slider for the user to adjust the exact split location.
If the split type is categorical, this input will contain boxes for each
unique value of the split_var. In the categorical case, the
checked boxes will be interpreted as category 1, while the unchecked
boxes will be category 0.
Include Information from Previous Wave allows
users to select if the displayed dataframe should be output from
optimum_allocation() or allocate_wave(). If
optimum_allocation() is chosen, it defaults to the
“WrightII” method with allow.na = TRUE. If
allocate_wave() is chosen, a new option to to select which
column contains the prior wave indicator will appear, and a valid column
(containing 0/1 or Y/N) must be selected. This choice corresponds to the
wave2a argument of allocate_wave().
n to sample allows users to indicate the number
of samples to be taken for the output dataframe. This selection
corresponds to the nsample argument of either
optimum_allocation() or allocate_wave(). Thus,
it should be different depending on which allocation function was
selected. For optimum_allocation(), it should be the total
number of samples to be taken, while for allocate_wave(),
it only indicates how many samples should be taken in the current
wave.
optimall_shiny() displays the output dataframe of
optimum_allocation() or allocate_wave() based
on the current inputs. After a split is confirmed and these inputs are
reset, it will show an error in place of this dataframe until valid
inputs are selected again. Displayed below this dataframe is a text list
of the code that performs each of the confirmed splits in
optimall.
When the user is satisfied with the parameters that are selected, a
split can be confirmed by pressing the Confirm Split button
at the bottom left of the page. This will split the existing data using
the split_strata() parameters specified in the inputs. The
inputs that specify arguments for the allocation will not change the
splits, they are only included to show how each split may impact the
sample allocation.
After Confirm Split is pressed, the code to perform that
split will appear in the output at the bottom right of the page. The
updated strata will now be in a column called “new_strata”, and the
inputs will reset. Using “new_strata” as the column defining the strata,
the user can then perform more splits, and the code to perform each one
will be added to the list at the bottom right with each
confirmation.
The splits in optimall_shiny() will not be performed on
the true dataset in the user’s optimall workflow in R.
Instead, the user must return to R if they want to actually transform
the data into a working dataframe with the new strata. The code
displayed in the app’s output makes this task simple, as it can be
copied and pasted into an R script to replicate the splits conducted in
the app. Note, however, that the data argument in each
split_strata() call needs to be changed to reflect the
user’s name for the data.
If any of the selected inputs results in an error in either
split_strata() or the selected allocation function, the app
will print the error.