Principles and practice in reporting structural equation analyses.
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.
McDonald
Roderick P
RP
Department of Psychology, University of Illinois at Urbana-Champaign, 61820, USA. rmcdonal@s.psych.uiuc.edu
Ho
Moon-Ho Ringo
MH
D006801:Humans; D016014:Linear Models; D008960:Models, Psychological; D012107:Research Design