mtscr_app: Shiny GUI for mtscr

View source: R/mtscr_app.R

mtscr_appR Documentation

Shiny GUI for mtscr


Shiny app used as graphical interface for mtscr. Simply invoke mtscr_app() to run.




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.


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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/aca0000571")}



mtscr documentation built on Nov. 2, 2023, 5:13 p.m.