Using Mokken scaling techniques to explore carelessness in survey research

Careless responding is a pervasive issue that impacts the interpretation and use of responses from survey instruments. Researchers have proposed numerous useful methods for detecting carelessness in survey research, including relatively simple summary statistics such as the frequency of adjacent responses in the same category (e.g., "long-string" analysis) and outlier statistics (e.g., Mahalanobis distance). Researchers have also used methods based on item response theory (IRT) models to identify examinees whose response patterns are unexpected given item parameters. However, researchers have not fully considered the use of nonparametric IRT methods based on Mokken scale analysis (MSA) to detect carelessness in survey research. MSA is a promising framework in which to consider participant carelessness because it is well suited to contexts in which parametric IRT models may not be appropriate, while still maintaining a focus on fundamental measurement requirements. We used a real data analysis and a simulation study to examine the sensitivity of MSA indicators of response quality to examinee carelessness and compared the results to those from standalone indicators. We also examined the impact of carelessness on the sensitivity of MSA item quality indicators. Numeric and graphical indicators of response quality from MSA indicators were sensitive to examinee carelessness. Graphical displays of nonparametric person response functions (PRFs) provided supplementary insight that can alert researchers to potentially problematic responses. Our results also indicated that MSA indicators of item quality are robust to the presence of participant carelessness. We consider the implications of our findings for research and practice.