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Summary

Confirmatory factor analysis (CFA) guidelines are presented for ordinal data, addressing limitations in SEM textbooks and software. This research offers practical solutions for accurate measurement model evaluation in social sciences.

Keywords:
LavaanConfirmatory factor analysisInternal structure validityJASPStructural equation modeling

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Area of Science:

  • Psychometrics
  • Quantitative Psychology
  • Structural Equation Modeling

Background:

  • Confirmatory Factor Analysis (CFA) is vital for measurement validity.
  • Ordinal data is common in social sciences but often overlooked in CFA methods.
  • Existing SEM software may lack adequate solutions for typical CFA with ordinal data.

Purpose of the Study:

  • To provide guidelines for conducting Confirmatory Factor Analysis (CFA) with ordinal data.
  • To address the gap in SEM literature and software for typical CFA applications.
  • To offer practical solutions for researchers using measurement instruments in social sciences.

Main Methods:

  • Conceptual contribution based on recent empirical research.
  • Development of a tutorial example using JASP and lavaan software.
  • Provision of supplementary materials (videos, files, scripts) for practical application.

Main Results:

  • Guidelines for conducting typical CFA with ordinal data are presented.
  • A practical tutorial demonstrates CFA implementation in JASP and lavaan.
  • The study highlights limitations in current SEM software for ordinal data analysis.

Conclusions:

  • This work offers conceptual and practical guidance for typical CFA with ordinal data.
  • Researchers can improve measurement model evaluation using the provided guidelines and tutorials.
  • Addressing software and textbook limitations enhances the accuracy of CFA in social sciences.