Shiny Apps for Automated Data Analysis and Automated Interpretation.

Introduction

The Statsomat/CFA app is a web-based application for automated Confirmatory Factor Analysis (CFA) based mainly on the R package lavaan and created with the Shiny technology. The Statsomat/CFA app is hosted on shinyapps.io and is one of several apps which can be accessed via the webpage of Statsomat (see https://statsomat.com), a nonprofit portal with the aim of developing, collecting and maintaining open-source apps for automated data analysis, interpretation and explanation. You can also access the app directly here https://statsomat.shinyapps.io/Confirmatory-factor-analysis/.

Installation

There is no need to install the Statsomat/CFA app since it runs in the browser. If you really want to run it locally, then clone the repository and run the app from the project folder:

shiny::runApp()

Before running the app locally, please consider to install required packages (check them in global.R and report_kernel.Rmd).

Example Usage

The dataset HolzingerSwineford1939.csv extracted from the R package lavaan is contained in the repository and can be used as an example. Select only the variables x1-x9 for a CFA. Type this model into the Type Your Model text area block, generate the report and finally download the report.

visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9

Follow also the Instructions described directly on the webpage of the app https://statsomat.shinyapps.io/Confirmatory-factor-analysis/.

Functionality

The user uploads its data as a CSV file, types the CFA model in lavaan model syntax directly in the browser and generates a PDF report. The report contains a data-driven interpretation and explanation of the CFA in plain English. The R code for the generation of the tables and graphics is included in the report and enables locally reproducibles results. The current version supports only approximately continuous data. Other restrictions to the data may apply.

Tests

The app was calibrated and tested by using the HolzingerSwineford1939 dataset contained in the R package lavaan and (simulated) data cases from literature.

Community

1. Contribute to the software: You are welcome to improve and extend the functionality of the app. If you want to make a pull request, please check that you can run test cases locally without any errors or warnings. Please consider to test your changes also on shinyapps.io. While uploading, ignore the Error in eval(x, envir = envir), it is a non-fatal error, also related to related to https://github.com/rstudio/packrat/issues/385 and https://github.com/rstudio/rsconnect/issues/429.

2. Report issues or problems with the software: Please open an issue in this repository to report any bugs.

3. Seek support: We try to answer all questions in reasonable time but general support is limited.