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| 頑健な調整済み媒介分析× | 構造方程式モデリング× | |
|---|---|---|
| 分野≠ | 統計学 | 研究統計 |
| 系統≠ | Latent structure | Process / pipeline |
| 提唱年≠ | 2007–2013 | 1921 |
| 提唱者≠ | Hayes, A. F.; building on Preacher, Rucker & Hayes (2007) for moderated mediation and robust bootstrap inference | Sewall Wright |
| 種類≠ | Conditional indirect effect model with robust inference | Method |
| 原典≠ | Hayes, A. F. (2022). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (3rd ed.). Guilford Press. ISBN: 978-1462549030 | Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm. link ↗ |
| 別名 | robust conditional process analysis, robust mediated moderation, robust moderated indirect effects, robust conditional indirect effects | SEM, path analysis, latent variable modeling, causal modeling |
| 関連≠ | 5 | 3 |
| 概要≠ | Robust moderated mediation tests whether the indirect effect of X on Y through a mediator M varies as a function of a moderator W, while using robust estimation (percentile or bias-corrected bootstrap, heteroscedasticity-consistent standard errors, or M-estimation) to protect inference against non-normality, outliers, and heteroscedasticity in the data. | Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis. |
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