Multilevel Factor Analysis: Reporting Guidelines and a Review of Reporting Practices

Area of Science:

• Multilevel factor analysis (MFA)
• Psychometric analysis
• Quantitative research methods

Background:

• Multilevel factor analysis (MFA) is increasingly used across disciplines.
• Existing reporting practices for MFA lack standardization.
• A systematic review is needed to assess current MFA application characteristics and reporting quality.

Purpose of the Study:

• To develop and propose reporting guidelines for multilevel factor analysis (MFA).
• To systematically review existing MFA applications to identify trends and assess adherence to best practices.
• To provide recommendations for improving the quality and transparency of MFA research.

Main Methods:

• Development of reporting guidelines for MFA.
• Systematic literature review of 72 MFA studies published between 1994 and 2014.
• Categorization of reviewed studies based on application characteristics, purpose, data source, statistical approach, and reported results.

Main Results:

• The review analyzed 72 MFA applications across diverse fields like education, health, management, and psychology.
• Results cover construct measurement, validation purposes, sample sizes (Level 1 and Level 2), statistical methods (e.g., maximum likelihood), and reported outcomes (e.g., ICCs, factor loadings, fit indices).
• Identified variations in reporting practices, suggesting a need for standardized guidelines.

Conclusions:

• The proposed reporting guidelines aim to enhance the clarity and reproducibility of MFA studies.
• Findings inform applied researchers on best practices for psychometric analyses within multilevel frameworks.
• The review provides a foundation for methodologists to investigate MFA issues using realistic data conditions.