RaschOnline: A web-based analysis platform for the Rasch rating scale model

The Rasch Rating Scale Model (RSM) is widely applied in questionnaire analysis, yet many Rasch software packages require installation and advanced technical expertise. This study presents RaschOnline, a web-based application deployed on Google App Engine that enables full RSM analysis through a browser interface. The system implements a streamlined three-step workflow—data upload, joint maximum likelihood estimation, and automated reporting. RaschOnline produces item and person parameter estimates, standard errors, and fit statistics, and provides essential diagnostic visualizations, including Wright maps, KIDMAP displays, category average plots, person outfit plots, and item dimension plots. All computations are performed on cloud-based infrastructure, ensuring platform independence and eliminating local software requirements. A simulation study demonstrates that RaschOnline yields item difficulty estimates and fit statistics comparable to those generated by Winsteps. These findings indicate that RaschOnline offers an accessible and scalable alternative for Rasch analysis in applied research and education.