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Latent change scores models for applied research: A practical guide using Mplus.

Michele Vecchione1, Antonio Zuffianò2

  • 1Department of Social and Developmental Psychology, Sapienza University of Rome, Rome, Italy.

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This guide introduces latent change scores (LCS) modeling for analyzing change over time. It covers basic and advanced applications, including dynamic relations between variables, with practical Mplus examples for researchers.

Keywords:
dual change scorelatent changelongitudinal studiespersonal values

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Area of Science:

  • Psychology
  • Quantitative Psychology
  • Statistical Modeling

Background:

  • Analyzing change over time is crucial in many scientific disciplines.
  • Structural equation modeling (SEM) provides a robust framework for such analyses.
  • Latent change scores (LCS) offer a flexible approach within SEM for modeling developmental and dynamic processes.

Purpose of the Study:

  • To provide a practical guide to modeling and interpreting latent change scores (LCS) models.
  • To introduce fundamental LCS concepts and extensions, including the dual change score (DCS) model.
  • To demonstrate applications using Schwartz's theory of basic personal values with Mplus software.

Main Methods:

  • Introduction to the basic univariate latent change score (LCS) model.
  • Extension to more complex models: dual change score (DCS), proportional change, and constant change models.
  • Application of bivariate LCS models to analyze dynamic relations between variables.

Main Results:

  • The article illustrates how LCS models can effectively determine growth trajectories across multiple assessment waves.
  • Bivariate LCS models are shown to be suitable for modeling the dynamic interplay between two variables.
  • Practical examples with Mplus syntax and output facilitate the implementation and interpretation of LCS models.

Conclusions:

  • Latent change scores (LCS) provide a powerful and adaptable tool for analyzing change in longitudinal data.
  • The presented guide equips students, researchers, and practitioners with the knowledge to apply LCS models effectively.
  • The use of Schwartz's theory of basic personal values demonstrates the broad applicability of LCS in psychological research.