Associate Professor & QM Area Chair
Office & Hours
Office: SZB 538H
Tues & Thurs
2 - 2:30 PM and 3:30 - 5 PM
or by appointment
The University of Texas at Austin
1912 Speedway, Stop D5800
Austin, TX 78712-1289
download vita (pdf)
Dr. Tiffany Whittaker’s research focuses on the examination and demonstration of various procedures used to model the relationships among variables, such as structural equation modeling (SEM), multilevel modeling (MLM), and item response theory (IRT) with an overarching focus on model specification.
B.A., Psychology, Criminal Justice, The University of Texas at San Antonio, 1995
M.S., Psychology, The University of Texas at San Antonio, 1998
Ph.D., Educational Psychology [Quantitative Methods], The University of Texas at Austin, 2003
Whittaker, T. A., Pituch, K. A., & McDougall, G. J. (in press). Latent growth modeling with domain-specific outcomes comprised of mixed response types in intervention studies. Journal of Consulting and Clinical Psychology.
Whittaker, T. A., Beretvas, S. N., & Falbo, T. (2014). Dyadic curve-of-factors model: An introduction and illustration of a model for longitudinal nonexchangeable dyadic data. Structural Equation Modeling, 21(1), 303-313.
Whittaker, T. A., & Khojasteh, J. (2013). A comparison of methods to detect invariant reference indicators in structural equation modeling. International Journal of Quantitative Research in Education, 1(4), 426-443.
Whittaker, T. A., Chang, W., & Dodd, B. G. (2013). The impact of varied discrimination parameters on mixed-format item response theory (IRT) model selection. Educational and Psychological Measurement, 73(3), 471-490.
Whittaker, T. A. (2013). The impact of noninvariant intercepts in latent means models. Structural Equation Modeling, 20(1), 108-130.
Whittaker, T. A., Chang, W., & Dodd, B. G. (2012). The performance of IRT model selection methods with mixed-format tests. Applied Psychological Measurement, 36(3), 159-180.
Whittaker, T. A. (2012). Using the modification index and standardized expected parameter change for model modification. Journal of Experimental Education, 80(1), 26-44.
Whittaker, T. A., Williams, N. J., & Dodd, B. G. (2011). Do examinees understand score reports for alternate methods of scoring computer based tests (CBTs)? Educational Assessment, 16(2), 69-89.
2014 - 2015, Fellow, Elizabeth Glenadine Gibb Teaching Fellowship in Education, College of Education, The University of Texas at Austin
Research Interests and Expertise
My principal methodological research interest deals with the various facets of model specification, including, but not limited to, model comparison/selection and model modification methods. With the use of simulation techniques, I examine the performance of these different model specification approaches under manipulated conditions. With the use of real data sets, I also provide illustrations and demonstrations of alternative model parameterizations for pedagogical purposes. There are numerous models that may be employed to explain the relationships among variables. I am interested in employing models within the structural equation modeling (SEM), multilevel modeling (MLM), and item response theory (IRT) arenas.
My other research interest deals with real-world data applications with these various modeling techniques. This is, in large part, due to requests from applied researchers to help with the methodological aspects of their study given my knowledge in quantitative methods. I enjoy these opportunities to collaborate with researchers in different disciplines because real-world data issues provide me with methodological research ideas as well as interesting examples to use in my courses when I am teaching.