Beyond path diagrams: Enhancing applied structural equation modeling research through data visualization.

ABSTRACT:

Introduction

Structural equation modeling (SEM) is a multivariate data analytic technique used in many domains of addictive behaviors research. SEM results are usually summarized and communicated through statistical tables and path diagrams, which emphasize path coefficients and global fit without showing specific quantitative values of data points that underlie the model results. Data visualization methods are often absent in SEM research, which may limit the quality and impact of SEM research by reducing data transparency, obscuring unexpected data anomalies and unmodeled heterogeneity, and inhibiting the communication of SEM research findings to research stakeholders who do not have advanced statistical training in SEM.

Methods and results

In this report, we show how data

SUBMITTER: Hallgren KA 

PROVIDER: S-EPMC6760248 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature