Reporting results from structural equation modeling analyses in Archives of Scientific Psychology.
Author(s) -
Rick H. Hoyle,
Jennifer C. Isherwood
Publication year - 2013
Publication title -
archives of scientific psychology
Language(s) - English
Resource type - Journals
ISSN - 2169-3269
DOI - 10.1037/arc0000004
Subject(s) - structural equation modeling , clarity , psychology , computer science , association (psychology) , data science , applied psychology , biochemistry , chemistry , machine learning , psychotherapist
Psychological research typically involves the analysis of data (e.g., questionnaire responses, records of behavior) using statistical methods. The description of how those methods are used and the results they produce is a key component of scholarly publications. Despite their importance, these descriptions are not always complete and clear. In order to ensure the completeness and clarity of these descriptions, the Archives of Scientific Psychology requires that authors of manuscripts to be considered for publication adhere to a set of publication standards. Although the current standards cover most of the statistical methods commonly used in psychological research, they do not cover them all. In this manuscript, we propose adjustments to the current standards and the addition of additional standards for a statistical method not adequately covered in the current standards-structural equation modeling (SEM). Adherence to the standards we propose would ensure that scholarly publications that report results of data analyzed using SEM are complete and clear.
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