Abstract
We introduce a shiny web application to facilitate the construction of Item Factor Analysis (a.k.a. Item Response Theory) models using the OpenMx package in the R statistical programming environment. The web application assists with importing data, outcome recoding, and model specification. The app does not conduct any analysis though. Instead, rmarkdown output is generated that serves dual purposes, to analyze a data set and model good programming practices. The app can be used as a teaching tool or as a starting point for custom analysis scripts.
Highlights
We introduce a shiny web application to facilitate the construction of Item Factor Analysis
OpenMx, a modular package originally designed for structural equation modeling (Neale et al, in press), recently gained the ability to handle Item Factor Analysis
A goal of OpenMx is to cater to the statistical power user and facilitate analyses that are difficult to conduct in other software, the development team is always on the lookout for ways to ease the learning curve for novice users as well
Summary
OpenMx, a modular package originally designed for structural equation modeling (Neale et al, in press), recently gained the ability to handle Item Factor Analysis We introduce a new shiny (RStudio and Inc., 2014) web application to generate OpenMx code in Rmarkdown format (Allaire et al, 2014). We believe this code generator substantially lowers the barrier to entry for novice users of Item Factor Analysis (IFA) and encourages a culture of literate programming (Knuth, 1984) and reproducible science (Peng, 2011; Nosek et al, 2015). The generated code can be customized at many levels This flexibility enables the production of custom analyses and reports as users grow more sophisticated in their modeling expectations
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