The Effects of Aberrant Responding on Model-Fit Assuming Different Underlying Response Processes.

ABSTRACT: Aberrant responding on tests and surveys has been shown to affect the psychometric properties of scales and the statistical analyses from the use of those scales in cumulative model contexts. This study extends prior research by comparing the effects of four types of aberrant responding on model fit in both cumulative and ideal point model contexts using graded partial credit (GPCM) and generalized graded unfolding (GGUM) models. When fitting models to data, model misfit can be both a function of misspecification and aberrant responding. Results demonstrate how varying levels of aberrant data can severely impact model fit for both cumulative and ideal point data. Specifically, longstring responses have a stronger impact on dimensionality for both ideal point and cumulative data, while rand

SUBMITTER: Reimers J 

PROVIDER: S-EPMC10552732 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature