ORIGINAL RESEARCH article
Front. Psychol.
Sec. Quantitative Psychology and Measurement
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1499076
Comparing Raw Score Difference, Multilevel Modeling, and Structural Equation Modeling Methods for Estimating Discrepancy in Dyads
Provisionally accepted
- 1Alexandria City Public Schools, Alexandria, Virginia, United States
- 2University of North Texas, Denton, United States
- 3Tarleton State University, Stephenville, Texas, United States
- 4Texas A and M University, College Station, Texas, United States
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Dyadic data analysis is commonly used in psychological research involving pairs of individuals in a nested relationship, such as parent and child, student and teacher, and pairs of spouses. Using a Monte Carlo simulation, the present study compared three methods for estimating discrepancy scores in dyad pairs: raw score difference (RSD), empirical Bayes estimates from multilevel modeling (MLM), and factor scores from structural equation modeling (SEM). Design factors for this simulation included intraclass correlation (ICC), cluster number, reliability estimates, effect size of discrepancy, and effect size variance. Results suggest discrepancy estimates from MLM had poor reliability compared to RSD and SEM methods, due in large part to the ICC, effect size variance, and cluster number design factors. RSD and SEM methods performed similarly, and are recommended for use in estimating discrepancy values, rather than MLM.
Keywords: dyadic analysis 1, dyadic discrepancy 2, multilevel modeling 3, structural equation modeling 4, Monte Carlo simulation 5
Received: 20 Sep 2024; Accepted: 22 Apr 2025.
Copyright: © 2025 McEnturff, Chen, Henson, Glaman and Luo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Qi Chen, University of North Texas, Denton, United States
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