paper/paper.md

In PsyChiLin/EFAshiny: EFAshiny : An User-friendly Application for Exploratory Factor Analysis

title: 'EFAshiny: An User-Friendly Shiny Application for Exploratory Factor Analysis' authors: - affiliation: 1 name: Chi-Lin Yu orcid: 0000-0002-4381-7163 - affiliation: 2 name: Ching-Fan Sheu orcid: 0000-0002-5978-5768 date: "8 February 2018" output: pdf_document bibliography: paper.bib tags: - Exploratory Factor Analysis (EFA) - Data Management - Data Visualization - R - Shiny - ggplot2 affiliations: - index: 1 name: Department of Psychology, National Taiwan University, Taiwan - index: 2 name: Institute of Education, National Cheng Kung University, Taiwan

Summary

EFAshiny is a user-friendly web application for exploratory factor analysis (EFA) [@efa]. The motivation to create EFAshiny is to streamline the routine work flow of EFA so that users unfamiliar with R can perform the analysis interactively in a web browser.

Employing the graphical user interface (GUI) of shiny [@shiny] framework (Figure 1), EFAshiny provides an integrated platform to perform EFA with a drop-down menu, offering a number of choices to manage, explore, analyze and visualize data. EFAshiny automates these processes by wrappings together several R [@r] packages, such as ggplot2 [@ggplot2], psych [@psych], psycho [@psycho], and EGA [@EGA], etc. For example, users can point-and-click to obtain graphical display of confidence intervals for factor loadings, which is not available in many commercial software. Moreover, results of analysis are presented on-line as tables and graphs and they can be saved and exported by the user.

Key features of EFAshiny include:

• An easy-to-use GUI to free users from scripting in R
• A step by step analysis flow to perform EFA
• Quick ways to summarize data by tables or graphs
• Several ways to explore factor retention numerically or graphically
• Several ways to explore factor extraction and rotation numerically or graphically
• A display of confidence intervals for factor loadings
• Several ways to link visualization of correlation matrix with factor structure
• Default options are chosen according to recommendations in the literature [@efaguide]
• A demonstration using a real psychological scale dataset

Although the EFAshiny application is primarily aimed at behavioral researchers who want to perform EFA on a set of associated variables (e.g., item-level scale dataset), it can also be used to explore FA-based connectivity analyses [@mclaughlin1992potential] in instrument data, such as event related potentials (ERPs) and functional near-infrared spectroscopy (fNIRS).

In conclusion, EFAshiny allows researchers to harness the combined power of many R packages together for performing interactive EFA and obtaining numerical and graphical results in a user-friendly menu-driven GUI. Documentation, tutorials and usages can be found on our page.

References

PsyChiLin/EFAshiny documentation built on May 27, 2019, 12:17 p.m.