Description
Methodologists have developed mediation analysis techniques for a broad range of substantive applications, yet methods for estimating mediating mechanisms with missing data have been understudied. This study outlined a general Bayesian missing data handling approach that can accommodate mediation analyses with any number of manifest variables.
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Contributors
- Enders, Craig (Author)
- Fairchild, Amanda J. (Author)
- MacKinnon, David (Author)
- College of Liberal Arts and Sciences (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2013
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Identifier
- Digital object identifier: 10.1080/00273171.2013.784862
- Identifier TypeInternational standard serial numberIdentifier Value0027-3171
- Identifier TypeInternational standard serial numberIdentifier Value1532-7906
Note
- "This is an Author's Accepted Manuscript of an article published in Multivariate Behavioral Research, 48(3), 340-369 2013 copyright Taylor & Francis, available online at: http://www.tandfonline.com/doi/abs/10.1080/00273171.2013.784862.", opens in a new window
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Enders, C. K., Fairchild, A. J., & MacKinnon, D. P. (2013). A bayesian approach for estimating mediation effects with missing data. Multivariate Behavioral Research, 48(3), 340-369. doi:10.1080/00273171.2013.784862