Tiffany Whittaker

Department Chair, Department of Educational Psychology
John L. and Elizabeth G. Hill Centennial Professorship (Fellow)

Phone: +1 512 471 2749
Email: t.whittaker@austin.utexas.edu
Office: SZB 5.308G, SZB
Office Hours: by appointment

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.

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.

Whittaker, T. A. (2019). The comparison of latent variable propensity score models to traditional propensity score models under conditions of covariate unreliability. Multivariate Behavioral Research. https://www-tandfonline-com.ezproxy.lib.utexas.edu/doi/full/10.1080/00273171.2019.1663136.

Lee, K. & Whittaker, T. A. (2018). Statistical power of the multiple domain latent growth model for detecting group differences. Structural Equation Modeling, 25(5), 700–714. (View)

Whittaker, T. A. & Khojasteh, J.. (2017). Detecting appropriate trajectories of growth in latent growth model comparisons: The performance of information-based criteria. Journal of Experimental Education, 85(2), 215–230. (View)

Boyle, L. H., Whittaker, T. A., Eval, M. & McCarthy, C. J. (2017). What really happens in group research? Results of a content analysis of recent quantitative research in JSGW. Journal for Specialists in Group Work, 42(3), 243–252. (View)

Pituch, K. A., Whittaker, T. A., Chang, W., Lockhart, L. & McDougall, G. J. (2016). Multivariate models for normal and binary responses in intervention studies. American Journal of Evaluation, 37(2), 270–286. (View)

Sanchez, D., Whittaker, T. A. & Hamilton, E. (2016). Perceived discrimination, peer influence and sexual behaviors in Mexican American preadolescent boys and girls: An examination of gender differences. Journal of Youth and Adolescence, 45(5), 928–944. (View)

Whittaker, T. A., Pituch, K. A. & McDougall, G. J. (2014). Latent Growth Modeling With Domain-Specific Outcomes Comprised of Mixed Response Types in Intervention Studies. Journal of Consulting and Clinical Psychology, 82(5), 746–759. (View)

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. (View)

Whittaker, T. A. & Khojasteh, J.. (2013). A comparison of methods to detect invariant reference indicators in structural equation modelling. International Journal of Quantitative Research in Education, 1(4), 426–443.

Judy Spence Tate Fellowship for Excellence, College of Education, The University of Texas at Austin (2018 - 2019)

Margie Gurley Seay Centennial Professorship in Education, College of Education, The University of Texas at Austin (2017 - 2018)

Excellence in Teaching Award, Department of Educational Psychology, The University of Texas at Austin (2015 - 2016)

Fellow in the H. E. Hartfelder/the Southland Corporation Regents Chair in Human Resource Development, College of Education, The University of Texas at Austin (2015 - 2016)

Elizabeth Glenadine Gibb Teaching Fellowship in Education, College of Education, The University of Texas at Austin (2014 - 2015)

Courses by year and semester
Year	Semester	Course
2024	Spring	EDP 380C: 14-Struct Equation Modeling
2023	Spring	EDP 380C: 14-Struct Equation Modeling
2022	Spring	EDP 380C: 14-Struct Equation Modeling
2021	Fall	EDP 381D: Advanced Statistical Modeling
2021	Spring	EDP 380C: 14-Struct Equation Modlng-Wb
2020	Fall	EDP 480C: 6-Stat Analysis: Exper Data-Wb
2020	Spring	EDP 380C: 14-Struct Equation Modeling
2019	Fall	EDP 380C: 8-Data Analysis Using Sas
2019	Fall	EDP 480C: 6-Stat Analysis: Exper Data
2019	Spring	EDP 380C: 14-Struct Equation Modeling
2019	Spring	EDP 381D: Advanced Statistical Modeling
2018	Fall	EDP 480C: 6-Stat Analysis: Exper Data
2018	Fall	EDP 380C: 14-Struct Equation Modeling
2018	Summer	EDP f480C: 6-Stat Analysis: Exper Data
2018	Spring	EDP 380C: 8-Data Analysis Using Sas
2017	Fall	EDP 380C: 6-Stat Analysis: Exper Data
2017	Spring	EDP 380C: 2-Fundamental Statistics
2017	Spring	EDP 380C: 14-Struct Equation Modeling
2016	Fall	EDP 380C: 6-Stat Analysis: Exper Data
2016	Fall	EDP 380C: 8-Data Analysis Using Sas
2016	Spring	EDP 380C: 14-Struct Equation Modeling
2015	Fall	EDP 380C: 4-Correlation/Regression Mthds
2015	Fall	EDP 380C: 8-Data Analysis Using Sas
2015	Spring	EDP 382K: 2-Correlation And Regresn Meth
2015	Spring	EDP 382K: 6-Structural Equation Modeling
2014	Fall	EDP 382K: 9-Adv Statistical Modeling
2014	Fall	EDP 384: 6-Data Analysis Using Sas
2014	Summer	EDP f482K: 1-Exper Design And Stat Infer
2014	Spring	EDP 371: Introduction To Statistics
2014	Spring	EDP 382K: 6-Structural Equation Modeling

Find Other Faculty