เปรียบเทียบวิธี

	การวิเคราะห์การส่งผ่านระดับพหุ	การวิเคราะห์การถ่ายทอดเหตุผลเชิงสาเหตุ (ผลกระทบโดยตรงและโดยอ้อมตามธรรมชาติ)	การวิเคราะห์กระบวนการแบบมีเงื่อนไข (การส่งผ่านแบบมีเงื่อนไข)	Hierarchical Linear Modeling
สาขาวิชา	สถิติศาสตร์	การอนุมานเชิงสาเหตุ	การอนุมานเชิงสาเหตุ	สถิติศาสตร์
ตระกูล	Hypothesis test	Regression model	Regression model	Hypothesis test
ปีกำเนิด	2003	2010	2018	1986
ผู้ริเริ่ม	Kenny, Korchmaros & Bolger	Pearl (2001); general framework by Imai, Keele & Tingley (2010)	Andrew F. Hayes (PROCESS framework); Preacher, Rucker & Hayes (moderated mediation)	Raudenbush & Bryk (popularized); Goldstein (parallel development)
ประเภท	Multilevel structural model	Counterfactual causal decomposition	Regression-based conditional process model	Parametric nested-data regression
แหล่งต้นตำรับ	Kenny, D. A., Korchmaros, J. D., & Bolger, N. (2003). Lower level mediation in multilevel models. Psychological Methods, 8(2), 115–128.	Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420.	Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). The Guilford Press. ISBN: 978-1462534654	Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049
ชื่อเรียกอื่น	multilevel mediation, hierarchical mediation, cross-level mediation, 1-1-1 mediation	natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation	moderated mediation, moderated mediation analysis, PROCESS model, Hayes PROCESS conditional process model	HLM, MLM, multilevel modeling, multilevel analysis
ที่เกี่ยวข้อง	8	5	5	4
สรุป	Multilevel mediation analysis is a parametric structural method that estimates indirect (mediated) effects within hierarchically nested data, such as students within schools or employees within organisations. Formalised for lower-level mediation in multilevel models by Kenny, Korchmaros and Bolger (2003), it simultaneously handles individual-level (1-1-1) and group-level (2-2-1 or 2-1-1) mediation pathways in a single coherent framework.	Causal mediation analysis is a counterfactual framework that splits a treatment's total effect into a Natural Direct Effect (NDE) and a Natural Indirect Effect (NIE) that runs through a mediator. The modern general approach was formalised by Pearl (2001) and Imai, Keele and Tingley (2010), giving the decomposition a precise causal interpretation.	Conditional process analysis is Andrew F. Hayes's regression-based PROCESS framework (2018) that combines mediation and moderation in a single model, testing how an indirect effect changes across levels of a moderator. It quantifies conditional indirect and conditional direct effects and tests them with bootstrap confidence intervals.	Hierarchical Linear Modeling (HLM), also known as Multilevel Modeling (MLM), is a parametric statistical method for analyzing nested or clustered data — for example students within classrooms, patients within hospitals, or employees within organizations. Formalized by Raudenbush and Bryk in their 2002 seminal text (building on work from the mid-1980s), HLM simultaneously estimates individual-level and group-level effects while correctly partitioning variance across levels.