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Classical & Bayesian Instrument Development

In order to use the software, you can (1) run it on our server directly from a web browser or (2) download and install several programs. If you would like to run it on our server from your web browser, go to: CBID Web Application. This is a great option if you want to get started right away! If you would like to run it on your own computer, follow these directions. We will assume you are using Windows, but you can use Google to find equivalent links for Linux. Note that if you are using a Mac, you will need to emulate Windows (via something such as WINE) because OpenBUGS is not available for Mac.

"Research reported in this publication was supported by the National Institute of Nursing Research of the National Institutes of Health under Award Number R03NR013236 (Principal Investigator: Dr. Byron Gajewski). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Use CBID or any reference sites at your own risk. The authors, NINR, and NIH are not responsible for uses of CBID."

STEP 1

Download and install the most recent versions of the following:

STEP 2

Open R Studio, type the following commands in the console (bottom left window) and press Enter. Alternatively, you can copy and paste all the install.package lines at once, paste them into the console, and press Enter to run them all at once:

  • install.packages("lavaan")
  • install.packages("psy")
  • install.packages("MCMCpack")
  • install.packages("boot")
  • install.packages("R2OpenBUGS")
  • install.packages("shiny")

depicts the RStudio console window displaying the command install.packages("lavaan") and its successful execution message: "package 'lavaan' successfully unpacked and MD5 sums checked." This indicates that the 'lavaan' package has been installed correctly in the R environment.

This installs the necessary packages. You will know each package has installed successfully if you see a message similar to: package 'lavaan' successfully unpacked and MD5 sums checked.

STEP 3

Save the file CBIDapp_0.1.tar.gz on your computer. Keep it saved as a .tar.gz file; do NOT extract its contents.

STEP 4

Use R Studio to install the CBID app:

  1. On the top-left, click "Tools", then select "Install Packages".
  2. For "Install from", choose "Package Archive File (.zip; .tar.gz)".

The image depicts the RStudio interface during the installation of the CBID application. The "Install Packages" dialog box is open, with the "Install from" option set to "Package Archive File (.zip; .tar.gz)" and the "Package Archive" field displaying the path to the "CBIDapp_0.1.tar.gz" file. This setup facilitates the installation of the CBID application from a local package archive file.

3) For "Package Archive", click browse, and select "CBIDapp_0.1.tar.gz" from wherever it is saved on your computer.

4) Click the install button.

STEP 5

Almost done! To run the app, enter the following lines in the console:

library(shiny)

library(CBIDapp)

run_CBID()

<pRStudio console showing execution of run_CBID() to initiate the CBID application.

After entering these commands, the CBID app should run. A tutorial describing how to use the software is available on the main page of the app:

The image displays the main interface of the CBID (Classical & Bayesian Instrument Development) application. It features a user-friendly layout with multiple tabs and input fields, allowing users to input data, select statistical models, and view results. The interface is designed to facilitate the development and analysis of psychometric instruments using both classical and Bayesian methods.

If you have any questions, feel free to email Sam Pepper at spepper@kumc.edu.

If you are interested in practicing with CBID, you can download a simulated data set. For Bayesian analysis, additional data sets are available: a prior data set and an expert data set.

We appreciate your feedback as CBID is currently undergoing usability testing. Please complete our short survey here: CBID Usability Survey.

KU School of Medicine

University of Kansas Medical Center
Department of Biostatistics & Data Science
3901 Rainbow Boulevard
Mailstop 1026
Kansas City, KS 66160