Exploratory structural equation modeling: a streamlined step by step approach using the R Project software.

Area of Science:

• Psychometrics
• Structural Equation Modeling
• Statistical Psychology

Background:

• Confirmatory Factor Analysis (CFA) has limitations in assessing multifactorial scales due to its assumption of unique item loadings.
• Exploratory Structural Equation Modeling (ESEM) integrates Exploratory Factor Analysis (EFA) and CFA, permitting cross-loadings for more realistic model assessment.
• ESEM adoption is hindered by software limitations and coding complexity.

Purpose of the Study:

• To present a streamlined, step-by-step tutorial for implementing Exploratory Structural Equation Modeling (ESEM).
• To provide both R and Mplus syntax for ESEM analysis, addressing software and coding barriers.
• To demonstrate ESEM by analyzing the factor structure of the Strengths and Difficulties Questionnaire (SDQ) using real-world data.

Main Methods:

• Utilized the open-source statistical software R for a tutorial on ESEM.
• Provided comparative syntax for both R and Mplus software packages.
• Applied ESEM to analyze the Strengths and Difficulties Questionnaire (SDQ) factor structure using data from the Longitudinal Study of Australian Children (LSAC).

Main Results:

• The tutorial successfully demonstrates a simplified sequence for ESEM analysis.
• Open-source R facilitates accessible implementation of ESEM procedures.
• Analysis of the SDQ using ESEM provides insights into its complex factor structure.

Conclusions:

• ESEM offers a more nuanced understanding of multidimensional scale structures compared to traditional CFA.
• This tutorial enhances the accessibility and application of ESEM in psychological research.
• Optimized ESEM application can improve the epidemiological and clinical assessment of psychiatric conditions.