A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort...

Area of Science:

• Psychometrics
• Quantitative Psychology
• Survey Methodology

Background:

• Careless and insufficient effort responding (C/IER) threatens the quality and validity of questionnaire data.
• Existing C/IER detection methods often target only specific patterns, failing to address the complexity of real-world data.

Purpose of the Study:

• To develop and present a unified model-based approach for detecting multiple manifestations of C/IER concurrently.
• To leverage response time (RT) data from computer-administered questionnaires for improved C/IER detection.

Main Methods:

• Integrated theoretical considerations of C/IER with psychometric modeling, incorporating the distance-difficulty hypothesis.
• Allowed for respondent- and screen-level variation in attentiveness, accommodating different trait and speed levels.
• Utilized item-level RTs and presented an adapted version for aggregated RTs for respondent-level screening.

Main Results:

• Investigated parameter recovery through a simulation study.
• Illustrated the approach with an empirical example, comparing various RT measures.
• Contrasted the proposed model-based procedure against traditional indicator-based multiple-hurdle approaches.

Conclusions:

• The proposed model-based approach offers a comprehensive method for detecting diverse C/IER patterns simultaneously.
• Leveraging RT data within a psychometric modeling framework enhances the ability to identify and account for C/IER, improving overall data quality.