HOW TO INFER MATHEMATICAL SEQUENTIAL MEDIATION RELATIONSHIPS FROM NETWORK ANALYSIS

Abstract

This paper explores the statistical inference of mathematical
sequential mediation relationships through network analysis,
utilizing JASP for network modeling and SPSS Process Macro
(Model 6) for mediation analysis. Sequential mediation analysis
is particularly useful when dealing with highly complex
theoretical models or when no theoretical model exists, enabling
exploratory or confirmatory studies of specific mediation
relationships. Network analysis serves as a complementary tool
to identify potential pathways and interrelations within variables
before applying mediation models. The paper includes an
applied example within a study that uses an extended Technology
Acceptance Model (TAM) to identify factors promoting TAM
adoption among preschool teachers. The methodological
implications of combining sequential mediation and network
analysis are discussed, offering significant contributions to the
behavioral sciences.