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Item Response Modeling of Clinical Instruments With Filter Questions: Disentangling Symptom Presence and Severity.

Brooke E Magnus¹

¹Boston College, Chestnut Hill, MA, USA.

Applied Psychological Measurement

|August 21, 2024

Summary

This summary is machine-generated.

The multivariate hurdle graded response model (MH-GRM) better measures psychopathology across all severity levels than traditional models, especially with excess zero data common in clinical instruments.

Keywords:

clinical assessment filter questions item response theory psychometrics zero inflation

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Area of Science:

Psychometrics
Psychopathology Measurement
Statistical Modeling

Background:

Clinical instruments with filter/follow-up formats often yield excess zero data.
Unidimensional graded response models (GRMs) struggle with zero-inflated data, underestimating individual differences at lower severity levels.

Purpose of the Study:

To evaluate the effectiveness of the multivariate hurdle graded response model (MH-GRM) for zero-inflated questionnaire data.
To compare the MH-GRM with unidimensional GRMs in capturing individual differences in psychopathology.

Main Methods:

Utilized simulated and empirical data containing excess zeros.
Applied both unidimensional GRMs and the proposed MH-GRM.
The MH-GRM incorporates two latent variables: susceptibility and severity.

Main Results:

The MH-GRM demonstrated superior ability to capture individual differences across a broader psychopathology spectrum compared to unidimensional GRMs.
Unidimensional GRMs, when applied to filter question data, largely failed to measure differences at lower severity levels.

Conclusions:

The MH-GRM is a more appropriate and comprehensive model for analyzing zero-inflated data from clinical instruments.
Accounting for excess zeros is crucial for accurately assessing individual differences in psychopathology across the full severity range.