Document Detail


Fitting data to model: structural equation modeling diagnosis using two scatter plots.
MedLine Citation:
PMID:  20853955     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts the residual-based M-distance with the quantile of a chi distribution. It allows the researcher to visually identify clusters of potential outliers. The article further studies the effect of the potential outliers on the overall model evaluation when they are removed according to the order of the clusters exhibited in the plot. Suggestions are provided on determining the outlier status of outstanding cases in real data analysis. Recommendations are also made on the choice of robust methods and maximum likelihood following outlier removal.
Authors:
Ke-Hai Yuan; Kentaro Hayashi
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Psychological methods     Volume:  15     ISSN:  1939-1463     ISO Abbreviation:  Psychol Methods     Publication Date:  2010 Dec 
Date Detail:
Created Date:  2010-12-07     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9606928     Medline TA:  Psychol Methods     Country:  United States    
Other Details:
Languages:  eng     Pagination:  335-51     Citation Subset:  IM    
Copyright Information:
PsycINFO Database Record (c) 2010 APA, all rights reserved.
Affiliation:
University of Notre Dame, Dame, IN 46556, USA. kyuan@nd.edu
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MeSH Terms
Descriptor/Qualifier:
Grant Support
ID/Acronym/Agency:
DA01070/DA/NIDA NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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