Revisiting the Estimation of Multilevel Modeling and Power Analysis for Multisite Randomized Trials

Zhenqiu Lu

DOI: 10.64028/tamc579799

Keywords: multilevel modeling estimation, multisite randomized trials, balanced and unbalanced design, power analysis

Abstract: Challenges arise in multisite randomized trials in power analysis and optimal design due to the complexities of random coefficients and hierarchical structures. To address these challenges, this article revisits the estimation of multilevel models (MLM). It presents various approaches to deriving parameter estimates, incorporating different algebraic derivations—basic or matrix algebra, along with different designs—balanced and unbalanced designs, different coding schemes for treatment and control groups, and some specific special cases. By showing the similarities, differences, and relationships among these estimates, the study provides a clearer framework, enhances transparency, and improves interpretability. Furthermore, by comparing the derived results with existing literature, it establishes connections that deepen researchers' understanding of MLM estimation in study design and power analysis.

Submission Number: 24