This open-source, R-based web application is suitable for educational and research purposes in experimental and quantitative sciences. It allows the creation of varied data sets with specified structures, such as between-group and within-participant variables, that can be categorical or continuous. These parameters can be set throughout the various tabs (sections) from the top menu. In the last tab, the data set can be downloaded. The benefits of this application include time-saving and flexibility in the control of parameters.
General guidelines include the following:
In the names of variables, it’s recommended only to use alphanumeric characters and underscore signs. The latter can be used to separate characters or words (e.g., variable_name). Different names should be used for each variable.
In the levels of categorical variables, alphanumeric, special characters and spaces are allowed.
In numeric fields (e.g., ‘Mean’, ‘Standard deviation’, ‘Relative probability [0, 1]’), only numbers and decimal points are allowed.
As the data set increases, so does the processing time.
More specific guidelines are available in each section.
Bernabeu, P., & Lynott, D. (2020). Web application for the simulation of experimental data (Version 1.4). https://github.com/pablobernabeu/Experiment-simulation-app/
This web application was developed in R (R Core Team, 2020). The code is available on Github, where contributions may be made. The initial code for this application was influenced by Section 5.7 (Simulating data for multi-factor designs) in Crump (2017). The R packages used include ‘dplyr’ (Wickham, François, Henry, & Müller, 2018), ‘DT’ (Xie, 2020), ‘flexdashboard’ (Iannone, Allaire, & Borges, 2020), ‘shiny’ (Chang, Cheng, Allaire, Xie, & McPherson, 2020) and ‘stringr’ (Wickham, 2019).
Options for development and local use of the app
Option A) Using local R/RStudio or RStudio Cloud project or Binder RStudio environment
[Step only necessary in R/RStudio] Install the packages in the versions used in the latest release of this application, by running:
install.packages('devtools') library(devtools) install_version('dplyr', '1.0.2', 'http://cran.us.r-project.org') install_version('DT', '0.15', 'http://cran.us.r-project.org') install_version('flexdashboard', '0.5.2', 'http://cran.us.r-project.org') install_version('htmltools', '0.5.0', 'http://cran.us.r-project.org') install_version('knitr', '1.30', 'http://cran.us.r-project.org') install_version('ngram', '3.0.4', 'http://cran.us.r-project.org') install_version('purrr', '0.3.4', 'http://cran.us.r-project.org') install_version('shiny', '1.5.0', 'http://cran.us.r-project.org') install_version('stringr', '1.4.0', 'http://cran.us.r-project.org') install_version('tidyr', '1.1.2', 'http://cran.us.r-project.org')
Open the index.Rmd script.
Run the application by clicking on ▶️ Run document at the top left, or by running
rmarkdown::run('index.Rmd')in the console.
Click on Open in Browser at the top left.
Option B) Using Dockerfile (see instructions)
Thank you to RStudio for the free hosting server used by this application, shinyapps.io.
Chang, W., Cheng, J., Allaire, J., Xie, Y., & McPherson, J. (2020). shiny: Web Application Framework for R. R package version 1.4.0. Available at http://CRAN.R-project.org/package=shiny.
Crump, M. J. C. (2017). Programming for Psychologists: Data Creation and Analysis (Version 1.1). https://crumplab.github.io/programmingforpsych/.
Iannone, R., Allaire, J. J., & Borges, B. (2020). Flexdashboard: R Markdown Format for Flexible Dashboards. http://rmarkdown.rstudio.com/flexdashboard.
R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Wickham, H. (2019). stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.4.0. https://CRAN.R-project.org/package=stringr.
Wickham, H., François, R., Henry, L., & Müller, K. (2018). dplyr: A Grammar of Data Manipulation. R package version 0.7.6. https://CRAN.R-project.org/package=dplyr.