ArticleApplied psychological measurement2018
A Zero-Inflated Box-Cox Normal Unipolar Item Response Model for Measuring Constructs of Psychopathology.
Article in Applied psychological measurement, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- The Devil Is in the Tail: Manchester Short Assessment of Quality of Life (MANSA) test percentiles and normalized T-scores.Journal of psychopathology and behavioral assessment · 2026Article
- Article
- Unipolar IRT and the Author Recognition Test (ART).Behavior research methods · 2024Article
- Item Response Modeling of Clinical Instruments With Filter Questions: Disentangling Symptom Presence and Severity.Applied psychological measurement · 2024Article
- Measuring Unipolar Traits With Continuous Response Items: Some Methodological and Substantive Developments.Educational and psychological measurement · 2024Article
- Measurement Invariant but Non-Normal Treatment Responses in Guided Internet Psychotherapies for Depressive and Generalized Anxiety Disorders.Assessment · 2023Article
- Exploration and analysis of a generalized one-parameter item response model with flexible link functions.Frontiers in psychology · 2023Article
- Symptom Presence and Symptom Severity as Unique Indicators of Psychopathology: An Application of Multidimensional Zero-Inflated and Hurdle Graded Response Models.Educational and psychological measurement · 2022Article
- DIF Detection With Zero-Inflation Under the Factor Mixture Modeling Framework.Educational and psychological measurement · 2022Article
- Multidimensional Computerized Adaptive Testing: A Potential Path Toward the Efficient and Precise Assessment of Applied Cognition, Daily Activity, and Mobility for Hospitalized Patients.Archives of physical medicine and rehabilitation · 2022Article
- Matching IRT Models to Patient-Reported Outcomes Constructs: The Graded Response and Log-Logistic Models for Scaling Depression.Psychometrika · 2021Review
- A study of alternative approaches to non-normal latent trait distributions in item response theory models used for health outcome measurement.Statistical methods in medical research · 2020Article
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Authors and funding
2 authors.
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Abstract
This research introduces a latent class item response theory (IRT) approach for modeling item response data from zero-inflated, positively skewed, and arguably unipolar constructs of psychopathology. As motivating data, the authors use 4,925 responses to the Patient Health Questionnaire (PHQ-9), a nine Likert-type item depression screener that inquires about a variety of depressive symptoms. First, Lucke's log-logistic unipolar item response model is extended to accommodate polytomous responses. Then, a nontrivial proportion of individuals who do not endorse any of the symptoms are accounted for by including a nonpathological class that represents those who may be absent on or at some floor level of the latent variable that is being measured by the PHQ-9. To enhance flexibility, a Box-Cox normal distribution is used to empirically determine a transformation parameter that can help characterize the degree of skewness in the latent variable density. A model comparison approach is used to test the necessity of the features of the proposed model. Results suggest that (a) the Box-Cox normal transformation provides empirical support for using a log-normal population density, and (b) model fit substantially improves when a nonpathological latent class is included. The parameter estimates from the latent class IRT model are used to interpret the psychometric properties of the PHQ-9, and a method of computing IRT scale scores that reflect unipolar constructs is described, focusing on how these scores may be used in clinical contexts.
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