Nonnormality of Data in Structural Equation Models
With the use of census block group data on sociodemographics, land use, and travel behavior, the cutoffs suggested in the literature for trustworthy estimates and hypothesis-testing statistics were tested, and the efficacy of deleting observations as an approach to improving multivariate normality in structural equation modeling was evaluated. It was found that the deletion of enough cases to achieve multivariate normality yielded results that were substantively different from those for the full sample and required that 17% of the sample be discarded. Alternatively, after only a few true outliers were deleted (0.8% of the sample), the measures of univariate and multivariate nonnormalities fell into the acceptable range for maximum likelihood estimation to be appropriate. The pursuit of a multivariate normal distribution by the deletion of observations should be consciously weighed against the loss of model power and generalizability in the interpretation of the results. That is, the analyst should proactively find the balance between the two extremes of (a) a model on the full sample that is unreliable because of extreme nonnormality and (b) a model on a sample that has discarded so many cases to achieve multivariate normality that it is no longer fully representative of the desired population. It is further argued that the process of finding that balance should be exposed to the audience rather than ignored or suppressed.
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Availability:
- Find a library where document is available. Order URL: http://www.trb.org/Main/Public/Blurbs/160630.aspx
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Authors:
- Gao, Shengyi
- Mokhtarian, Patricia L
- Johnston, Robert A
- Publication Date: 2008
Language
- English
Media Info
- Media Type: Print
- Features: Figures; References; Tables;
- Pagination: pp 116-124
- Monograph Title: Travel Behavior Analysis 2008
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Serial:
- Transportation Research Record: Journal of the Transportation Research Board
- Issue Number: 2082
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Data collection; Estimation theory; Maximum likelihood method; Multivariate analysis; Normal distributions; Statistical analysis; Structural equation modeling; Travel behavior; Travel surveys
- Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01099523
- Record Type: Publication
- ISBN: 9780309125994
- Files: TRIS, TRB
- Created Date: May 21 2008 7:08AM