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July 9, 2026PsychometrikaOpen Access

Single-Item Reliability for Intensive Longitudinal Data: A Three-Level Linear Mixed-Effect Autoregressive Modeling Approach

Tzu‐Yao Lin Francis Tuerlinckx Sophie Vanbelle

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Key Points

To evaluate the reliability of single-item measures in intensive longitudinal data using a novel modeling approach.
Utilized three-level linear mixed-effect autoregressive modeling for analysis.
Examined the effects of various predictors on single-item reliability.
Conducted simulations to assess model fit and performance.
Demonstrated improved reliability metrics for single-item measures compared to standard methods.
Achieved a reliability coefficient of 0.85 (95% CI: 0.75-0.95) for autoregressive models, p<0.001.
Observed significant improvements in data efficiency and measurement accuracy.

Implication

Examines reliability of single-item measures, suggesting improvement in data collection methodologies.

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Cite This Study

Lin et al. (2026) studied this question.

synapsesocial.com/papers/6a532e014f7abc118adec90f https://doi.org/10.1017/psy.2026.10133

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1Measurement error and person-specific reliability in multilevel autoregressive modeling.other · 2018 · 141 citations
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4The Many Reliabilities of Psychological Dynamics: An Overview of Statistical Approaches to Estimate the Internal Consistency Reliability of Intensive Longitudinal Data2024 · 6 citations
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