Editorial: Recent Advancements in Structural Equation Modeling (SEM): From Both Methodological and Application Perspectives

Frontiers in Psychology

Oi-Man Kwok¹ 

关键词: structural equating modeling;    measurement invariance (MI);    multilevel (ML);    Mediation;    meta analysis;    effect size;    complex data;   

DOI  :  10.3389/fpsyg.2018.01936

学科分类：心理学（综合）

来源: Frontiers

【 摘 要 】

Structural equation modeling (SEM) is becoming the central and most popular analytical tool in the social sciences. Many classical and modern statistical techniques such as regression analysis, path analysis, confirmatory factor analysis, and models with both measurement and structural components have been shown to fall under the umbrella of SEM. Thus, the flexibility of SEM makes it applicable to many research designs, including experimental and non-experimental data, cross-sectional and longitudinal data, and multiple-group and multilevel data. Further enhancing the popularity and widespread use of SEM, it has recently experienced exciting advancements—from fundamental issues like alternative estimation methods that are robust to often violated assumptions to the expansion of SEM to incorporate multilevel and cross-classified data that are common in the social sciences. This Special Research Topic aims to bring in a collection of SEM papers that not only tackle technical estimation issues but also examine and demonstrate application of SEM to more complex settings, such as applying robust estimation method, testing interaction effect, examining measurement invariance, and specifying and evaluating models applied to different types of data, including meta-analytic data, multilevel, and longitudinal data.

【 授权许可】

CC BY