The Sampling Ratio in Multilevel Structural Equation Models: Considerations to Inform Study Design.

ABSTRACT: Multilevel structural equation modeling (MSEM) allows researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This article explores how variation in the sampling ratio in MSEM affects the measurement of Level 2 (L2) latent constructs. Specifically, we investigated whether the sampling ratio is related to bias and variability in aggregated L2 construct measurement and estimation in the context of doubly latent MSEM models utilizing a two-step Monte Carlo simulation study. Findings suggest that while lower sampling ratios were related to increased bias, standard errors,

SUBMITTER: Kush JM 

PROVIDER: S-EPMC9014731 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature