mtscr_app {mtscr} | R Documentation |
Shiny GUI for mtscr
Description
Shiny app used as graphical interface for mtscr. Simply invoke mtscr_app()
to run.
Usage
mtscr_app()
Details
To use the GUI you need to have the following packages installed:
DT
, broom.mixed
, datamods
, writexl
.
First thing you see after running the app is datamods
window for importing your data.
You can use the data already loaded in your environment or any other option.
Then you'll see four dropdown lists used to choose arguments for mtscr_model()
and mtscr_score()
functions. Consult these functions' documentation for
more details (execute ?mtscr_score
in the console). When the parameters are chosen,
click "Generate model" button. After a while (up to a dozen or so seconds) models'
parameters and are shown along with a scored dataframe.
You can download your data as a .csv or an .xlsx file using buttons in the sidebar.
You can either download the scores only (i.e. the dataframe you see displayed) or
your whole data with .all_max
and .all_top2
columns added.
For testing purposes, you may use mtscr_creativity
dataframe. In the importing
window change "Global Environment" to "mtscr" and our dataframe should appear
in the upper dropdown list. Use id
for the ID column, item
for the item
column and SemDis_MEAN
for the score column.
Value
Runs the app. No explicit return value.
See Also
mtscr_score()
for more information on the arguments.
mtscr_creativity for more information about the example dataset.
Forthmann, B., Karwowski, M., & Beaty, R. E. (2023). Don’t throw the “bad” ideas away! Multidimensional top scoring increases reliability of divergent thinking tasks. Psychology of Aesthetics, Creativity, and the Arts. doi:10.1037/aca0000571
Examples
if(interactive()){
mtscr_app()
}