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A Latent Variable Mixed-Effects Location Scale Model with an Application to Daily Diary Data.

Shelley A Blozis1

  • 1Department of Psychology, University of California, One Shields Avenue, Davis , CA 95616, USA. sablozis@ucdavis.edu.

Psychometrika
|May 3, 2022
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Summary

This study introduces a new statistical model to analyze individual changes over time and differences between people. The model helps understand variations in common factors, like positive affect, using daily stressor data.

Keywords:
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Area of Science:

  • Psychological statistics
  • Longitudinal data analysis
  • Mixed-effects modeling

Background:

  • Repeated measures data present challenges in distinguishing within-person fluctuations from between-person differences.
  • Traditional mixed-effects models offer insights into variance but may not fully capture complex relationships in longitudinal data.
  • Understanding predictors of both within- and between-person variance is crucial for comprehensive analysis.

Purpose of the Study:

  • To develop a novel statistical framework, the latent variable mixed-effects location scale model (LVM-ESLM), for analyzing longitudinal data.
  • To characterize and model both within- and between-person variation in a latent common factor.
  • To apply the proposed model to examine daily positive affect and stressors in adult women.

Main Methods:

  • Development of a latent variable mixed-effects location scale model (LVM-ESLM).
  • Integration of a longitudinal common factor model with a mixed-effects location scale model.
  • Application of the LVM-ESLM to a dataset of daily positive affect and daily stressors from a large sample of adult women.

Main Results:

  • The LVM-ESLM effectively characterizes within- and between-person variation in a common factor.
  • The model allows for the investigation of predictors influencing both within-person and between-person variances.
  • Illustrative analysis demonstrated the model's utility in understanding the interplay of daily affect and stressors.

Conclusions:

  • The proposed LVM-ESLM provides a powerful tool for dissecting within- and between-person variability in longitudinal studies.
  • This approach enhances the understanding of dynamic processes and individual differences in psychological research.
  • The model's application highlights its potential for analyzing complex daily diary data and informing psychological interventions.