Principles and practice in reporting structural equation analyses.

TLDR

Structural equation modeling reporting guidelines are reviewed to provide readers with complete and accurate information. The paper recommends that reports include a detailed justification of the model, plausible alternatives, identifiability, handling of nonnormality and missing data, and a complete set of parameters, standard errors, correlation matrix, discrepancies, and goodness‑of‑fit indices to enable independent critical judgment. The authors surveyed representative studies to compare current reporting practices with the recommended principles.

Abstract

Principles for reporting analyses using structural equation modeling are reviewed, with the goal of supplying readers with complete and accurate information. It is recommended that every report give a detailed justification of the model used, along with plausible alternatives and an account of identifiability. Nonnormality and missing data problems should also be addressed. A complete set of parameters and their standard errors is desirable, and it will often be convenient to supply the correlation matrix and discrepancies, as well as goodness-of-fit indices, so that readers can exercise independent critical judgment. A survey of fairly representative studies compares recent practice with the principles of reporting recommended here.