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This review introduces meta-analytic structural equation modeling (MASEM) for child development research. An application in reading comprehension (RC) development demonstrates its utility for analyzing large datasets and understanding developmental factors.

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Area of Science:

  • Developmental Psychology
  • Quantitative Psychology
  • Educational Psychology

Background:

  • Meta-analytic structural equation modeling (MASEM) is an advanced statistical technique.
  • Understanding child development requires robust analytical methods to synthesize findings from multiple studies.

Purpose of the Study:

  • To introduce the meta-analytic structural equation modeling (MASEM) technique to researchers in child development.
  • To discuss the utility and application of MASEM in studying developmental processes.
  • To examine the factor structure and relationships among reading comprehension components using MASEM.

Main Methods:

  • MASEM employs a two-stage approach: generating a composite correlation matrix and fitting a priori models.
  • A large-scale application involved analyzing data from 155 studies with over 1.2 million students (ages 3.5-46.225).
  • The study investigated the factor structure and interrelations of reading comprehension components.

Main Results:

  • MASEM provides a robust framework for integrating findings across numerous studies.
  • The application successfully analyzed the complex factor structure of reading comprehension development.
  • Significant relationships among reading comprehension components were identified.

Conclusions:

  • MASEM is a valuable technique for advancing the study of child development, particularly for synthesizing complex data.
  • The findings highlight the utility of MASEM in understanding developmental trajectories, such as in reading comprehension.
  • Further application of MASEM can enhance developmental research methodologies.