Faculty Member: Thomas, Roland

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Two new methods for estimating structural equation models: An illustration and a comparison with two established methods

Lu, I. R. R., Kwan, E., Thomas, D. R. and M. Cedzynski (2011), “Two new methods for estimating structural equation models: An illustration and a comparison with two established methods”, International Journal of Research in Marketing, 28(3), 258-268.

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The comparison of Component- and Covariance-based Structural Equation Modeling Approaches: Bias and Confidence Interval Coverage

Lu, I. R. R., Thomas, D. R., and E. Kwan (2009), “The comparison of Component- and Covariance-based Structural Equation Modeling Approaches: Bias and Confidence Interval Coverage”, 16th International Meeting of the Psychometric Society, Cambridge, U.K.

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Measuring country image: A research proposal

Lu, I. R. R., Heslop, L.A. and D.R. Thomas (2008), “Measuring country image: A research proposal”. Annual Conference of Administrative Sciences Association of Canada, Marketing Division, Halifax, Nova Scotia, May 24-27.

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Workplace Bullying in Academia: A Canadian Study

McKay, R., D. Huberman-Arnold, J. Fratzl, D.R. Thomas (2008), “Workplace Bullying in Academia: A Canadian Study”. Employee Rights and Responsibilities Journal, 20(2), 77-100. (http://dx.doi.org/10.1007/s10672-008-9073-3).

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The PLS-CBSEM Debate and an Investigation of Alternative Modeling Methods

Lu, I. R. R., D.R Thomas, E. Kwan and M. Cedzynski (2008), “The PLS-CBSEM Debate and an Investigation of Alternative Modeling Methods”. Joint Statistical Meetings, Denver, Colorado.

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Point estimates and confidence intervals for variable importance in multiple linear regression

Thomas, D.R., P.C. Zhu and Y.J. Decady (2007), “Point estimates and confidence intervals for variable importance in multiple linear regression”. Journal of Behavioral and Educational Statistics, 32(1), 61-91.

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Bayesian methods in management research: An application to logistic regression

Wylie, J., Muegge, S. M. and D.R. Thomas (2006), “Bayesian methods in management research: An application to logistic regression”. Proceedings, Administrative Sciences Association of Canada, Management Science Division, Banff, Alta.

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Variable importance in logistic regression based on partitioning an R2 measure

Thomas, D.R., P.C. Zhu, S. Dutta, and B.D. Zumbo (2006), “Variable importance in logistic regression based on partitioning an R2 measure”. Proceedings, Administrative Sciences Association of Canada, Management Science Division, Banff, Alta.

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Point estimates and confidence intervals for variable importance in multiple linear regression

Thomas, D.R., P.C. Zhu, and Y.J. Decady (2006), “Point estimates and confidence intervals for variable importance in multiple linear regression”. Journal of Behavioral and Educational Statistics. (in press).

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Partial Least Squares: A critical review and a potential alternative

Thomas, D.R., I.R.R. Lu, and M. Cedzynski (2005), “Partial Least Squares: A critical review and a potential alternative”. Proceedings, Administrative Sciences Association of Canada, Management Science Division, Toronto.

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