What question did this study set out to answer?

To develop a latent class location-scale regression model for analyzing longitudinal behavioral data with hidden patterns in mean and variability.

A latent class location-scale regression model with an application to calorie intake data

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To develop a latent class location-scale regression model for analyzing longitudinal behavioral data with hidden patterns in mean and variability.
Utilized a full Bayesian approach with Stan for parameter estimation.
Conducted simulation studies to evaluate model performance.
Applied the model to calorie intake data from a weight loss management study.
Demonstrated improved precision and informativeness in estimating scale parameters.
Achieved high correct classification rates without over-identifying latent classes.
Provided insights into dietary behavior consistency for personalized interventions.

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Innovative model identifies hidden patterns in calorie intake variability for weight management, suggesting effective interventions.

Zhang et al. (2026) studied this question.

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