Try the CA-BAT here! http://shiny.pmcharrison.com/cabat-demo
When using the CA-BAT in your own research, you can cite the original CA-BAT research paper:
Harrison, P. M. C., & Müllensiefen, D. (2018). Development and validation of the Computerised Adaptive Beat Alignment Test (CA-BAT). Scientific Reports, 8(12395), 1–19. https://doi.org/10.1038/s41598-018-30318-8
and this implementation:
Harrison, P. M. C., & Müllensiefen, D. (2018). Computerised Adaptive Beat Alignment Test (CA-BAT), psychTestR implementation. Zenodo. https://doi.org/10.5281/zenodo.1415353
We also advise mentioning the software versions you used,
in particular the versions of the
You can find these version numbers from R by running the following commands:
library(cabat) library(psychTestR) library(psychTestRCAT) if (!require(devtools)) install.packages("devtools") x <- devtools::session_info() x$packages[x$packages$package %in% c("cabat", "psychTestR", "psychTestRCAT"), ]
We are grateful to the following individuals for translating the CA-BAT into new languages:
If you don't have R installed, install it from here: https://cloud.r-project.org/
Install the ‘devtools’ package with the following command:
You can demo the melodic discrimination test at the R console, as follows:
# Load the cabat package library(cabat) # Run a demo test, with feedback as you progress through the test, # and not saving your data demo_cabat() # Run a demo test, skipping the training phase, and only asking 5 questions demo_cabat(num_items = 5, take_training = FALSE)
standalone_cabat() function is designed for real data collection.
In particular, the participant doesn't receive feedback during this version.
# Load the cabat package library(cabat) # Run the test as if for a participant, using default settings, # saving data, and with a custom admin password standalone_cabat(admin_password = "put-your-password-here")
You will need to enter a participant ID for each participant. This will be stored along with their results.
Each time you test a new participant,
and a new participation session will begin.
You can retrieve your data by starting up a participation session, entering the admin panel using your admin password, and downloading your data. For more details on the psychTestR interface, see http://psychtestr.com/.
The CA-BAT currently supports English (EN), French (FR), German (DE), Russian (RU),
Spanish (ES), and Italian (IT).
If you would like to add a new language to this list, please contact us.
You can select one of these languages by passing a language code as
an argument to
standalone_cabat(languages = "DE"),
or alternatively by passing it as a URL parameter to the test browser,
eg. http://127.0.0.1:4412/?language=DE (note that the
p_id argument must be empty).
Please note that the demo version of the test (
currently only supports English.
The main output from the CA-BAT is an
corresponding to the ability estimate for the participant.
It is computed from the underlying item response model and ranges approximately from -4 to +4.
A secondary output is an
corresponding to the standard error of measurement for the ability estimate;
again, it is computed from the underlying IRT model.
For most applications you would only use the
unless using a statistical analysis technique that allows you to specify measurement error explicitly.
For more information about item response theory, see the Wikipedia article;
for more information about CA-BAT scores, see
Harrison & Müllensiefen, 2018.
psychTestR provides several ways of retrieving test results (see http://psychtestr.com/). Most are accessed through the test's admin panel.
compile_trial_by_trial_results()from the R console (having loaded the CA-BAT package using
?compile_trial_by_trial_results()for more details.
readRDS(). Detailed results are stored as the 'metadata' attribute for the ability field. You can access it something like this:
x <- readRDS("output/results/id=1&p_id=german_test&save_id=1&pilot=false&complete=true.rds") attr(x$BAT$ability, "metadata")
sudo mkdir cabat
Make a text file in this folder called
specifying the R code to run the app.
To open the text editor:
sudo nano cabat/app.R
library(cabat) standalone_cabat(admin_password = "put-your-password-here")
Save the file (CTRL-O).
Change the permissions of your app directory so that
can write its temporary files there.
sudo chown -R shiny cabat
shiny is the username for the Shiny process user
(this is the usual default).
Versions <= 0.3.0 of this package experimented with weighted likelihood ability estimation for item selection. However, current versions of the package revert to Bayes modal ability estimation for item selection, for consistency with the original CA-BAT paper.
data-raw/dict-spanish.csv for an example of a foreign-language dictionary.
Create a new dictionary for your new language following this format.
Prepare a merge request for submitting your changes,
perhaps using a fork of the original repository.
Place the file in
data-raw/cabat-dict.R, adding a new four-line section for your new language,
following the lines used to add previous languages.
Run the file and commit the changes to Git.
cabat_languages function in
languages.R to include the new language.
Update the languages section in
README.md to credit the translator.
Rebuild the R package locally and test that you can use the test with
your new translations.
Submit your changes as a merge request.
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