Croon's Bias-Corrected Factor Score Path Analysis for Small- to Moderate-Sample Multilevel Structural Equation Models

2021
Maximum likelihood estimation of multilevel structural equation model (MLSEM) parameters is a preferred approach to probe theories involving latent variables in multilevel settings. Although maximum likelihood has many desirable properties, a major limitation is that it often fails to converge and can incur significant bias when implemented in studies with a small to moderate multilevel sample (e.g., fewer than 100 organizations with 10 or less individuals/organization). To address similar limitations in single-level SEM, literature has developed Croon's bias-corrected factor score path analysis estimator that converges more regularly than maximum likelihood and delivers less biased parameter estimates with small to moderate sample sizes. We derive extensions to this framework for MLSEMs and probe the degree to which the estimator retains these advantages with small to moderate multilevel samples. The estimator emerges as a useful alternative or complement to maximum likelihood because it often outperforms maximum likelihood in small to moderate multilevel samples in terms of convergence, bias, error variance, and power. The proposed estimator is implemented as a function in R using lavaan and is illustrated using a multilevel mediation example.
ORGANIZATIONAL RESEARCH METHODS
页码:55-77|卷号:24|期号:1
ISSN:1094-4281
收录类型
SSCI
发表日期
2021
学科领域
循证经济学
国家
美国
语种
英语
DOI
10.1177/1094428119879758
其他关键词
RANDOMIZED-TRIALS; STATISTICAL POWER; MEDIATION; REGRESSION; CONSEQUENCES; PRECISION; ACCURACY; WORK; SIZE
EISSN
1552-7425
资助机构
National Science FoundationNational Science Foundation (NSF) [1552535, 1760884]
资助信息
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the National Science Foundation (grant numbers 1552535, 1760884). The National Science Foundation had no role or involvement in the conduct of the research or the preparation of the manuscript.
被引频次(WOS)
5
被引更新日期
2022-01
来源机构
University of Cincinnati University of North Carolina University of North Carolina Charlotte University of North Carolina University of North Carolina Chapel Hill
关键词
Croon limited information estimator full information estimator maximum likelihood structural equation models unreliability measurement error multilevel models factor score regression