This study examines the methodology of causal modeling for data in which each environment was evaluated by multiple subjects. The results are as follows; 1) The reasons for difference between interclass effect and intraclass effect were organized as five mechanisms. 2) The method was proposed to correct the tendency for statistical tests as single-level model to become loose. 3) As a case study, ML-SEM were applied to some survey data, and the application method of ML-SEM and its effectiveness were shown.
|Translated title of the contribution||CAUSALITY ANALYSIS ON ENVIRONMENTAL EVALUATION (PART 4): CAUSAL MODELING FOR MULTILEVEL DATA OF ENVIRONMENT AND INDIVIDUAL - Application of Multilevel-SEM and proposal of adjustment technique for statistical tests -|
|Number of pages||12|
|Journal||Journal of Environmental Engineering (Japan)|
|Publication status||Published - 2022 Jun|
ASJC Scopus subject areas
- Environmental Engineering