ArticlePsychometrika2022
A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data.
Article in Psychometrika, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers.
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27 citing papers in PubMed, 73 citations in OpenAlex.
- Accounting for response styles in rating data using IRT and IRTree models: A tutorial in R with applications to self-reported metacognitive competence.Behavior research methods · 2026Article
- Understanding when mixture models effectively identify careless responding: Simulation and validity evidence.Behavior research methods · 2026Article
- Dependent latent class partial credit models for careless and insufficient effort responding in online survey data.Behavior research methods · 2026Article
- Joint partial credit and time model.Behavior research methods · 2026Article
- Investigating dynamics in attentive and inattentive responding together with their contextual correlates using a novel mixture IRT model for intensive longitudinal data.The British journal of mathematical and statistical psychology · 2026Article
- Faking in High-Stakes Personality Assessments: A Response-Time-Based Latent Response Mixture Modeling Approach.Educational and psychological measurement · 2026Article
- Robust Estimation of Polychoric Correlation.Psychometrika · 2025Article
- A modified hidden Markov model for detecting insufficient effort responses in questionnaires.Behavior research methods · 2025Article
- Bayesian factor mixture modeling with response time for detecting careless respondents.Behavior research methods · 2025Article
- A Beta Mixture Model for Careless Respondent Detection in Visual Analogue Scale Data.Psychometrika · 2025Article
- Accounting for Persistence in Tests with Linear Ballistic Accumulator Models.Psychometrika · 2025Article
- Validation of the Russian version of the realistic moral vignettes for studies of moral judgments.Behavior research methods · 2025Article
- Polytomous explanatory item response models for item discrimination: Assessing negative-framing effects in social-emotional learning surveys.Behavior research methods · 2025Article
- Oncology Healthcare Providers' Knowledge, Attitudes, and Practices Regarding Chemotherapy-Induced Myelosuppression in Ovarian Cancer in Haikou, China.Journal of multidisciplinary healthcare · 2025Article
- The Impact of Insufficient Effort Responses on the Order of Category Thresholds in the Polytomous Rasch Model.Educational and psychological measurement · 2024Article
- Detecting inattentive respondents by machine learning: A generic technique that substitutes for the directed questions scale and compensates for its shortcomings.Behavior research methods · 2024Article
- Detecting Careless Responding in Multidimensional Forced-Choice Questionnaires.Educational and psychological measurement · 2024Article
- Co-occurring dominance and ideal point processes: A general IRTree framework for multidimensional item responding.Behavior research methods · 2024Article
- Temporal dynamics in psychological assessments: a novel dataset with scales and response times.Scientific data · 2024Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Careless and insufficient effort responding (C/IER) can pose a major threat to data quality and, as such, to validity of inferences drawn from questionnaire data. A rich body of methods aiming at its detection has been developed. Most of these methods can detect only specific types of C/IER patterns. However, typically different types of C/IER patterns occur within one data set and need to be accounted for. We present a model-based approach for detecting manifold manifestations of C/IER at once. This is achieved by leveraging response time (RT) information available from computer-administered questionnaires and integrating theoretical considerations on C/IER with recent psychometric modeling approaches. The approach a) takes the specifics of attentive response behavior on questionnaires into account by incorporating the distance-difficulty hypothesis, b) allows for attentiveness to vary on the screen-by-respondent level, c) allows for respondents with different trait and speed levels to differ in their attentiveness, and d) at once deals with various response patterns arising from C/IER. The approach makes use of item-level RTs. An adapted version for aggregated RTs is presented that supports screening for C/IER behavior on the respondent level. Parameter recovery is investigated in a simulation study. The approach is illustrated in an empirical example, comparing different RT measures and contrasting the proposed model-based procedure against indicator-based multiple-hurdle approaches.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.