Using Mplus to detect careless responses with the help of a simple-to-use online application

Careless responding poses a notable challenge in measurement due to its potential to distort relationships between items. Factor mixture modeling, as a statistical modeling tool adept at identifying heterogeneous clusters within a population, has emerged as a promising avenue for careless-responding detection. The recent development of three factor mixture models, by Arias et al., Steinmann et al., and Kam and Cheung has advanced the field of careless-responding detection. All three models have been demonstrated to be effective. However, the application of these factor mixture models necessitates familiarity with the syntax for mixture modeling in Mplus, which can be inconvenient to novice Mplus users. To facilitate the convenient and rapid deployment of factor mixture models for careless-responding detection, this study has developed a user-friendly online application for the three factor mixture models to help users generate the necessary Mplus syntax.