Sonya K. Sterba
Associate Professor of Psychology and Human Development
Director, Quantitative Methods Program
My research topics include latent variable models for longitudinal and cross-sectional data, mixture models, and multilevel models, with a focus on advancing psychology research.
- Sterba, S.K. (2019). Problems with rationales for parceling that fail to consider parcel-allocation variability. Multivariate Behavioral Research, 54, 264-287.
- Rights, J.D., & Sterba, S.K. (2019). Quantifying explained variance in multilevel models: An integrative framework for defining R-squared measures. Psychological Methods, 24, 309-338. Online appendix and code available.
- Preacher, K.J., & Sterba, S.K. (2019). Aptitude-by-treatment interactions in research on educational interventions. Exceptional Children, 85, 248-254.
- Rights, J.D., & Sterba, S.K. (2018). A framework of R-squared measures for single-level and multilevel regression mixture models. Psychological Methods, 23, 434-457. Online appendix and code available.
- Lee, W.-y., Cho, S.-J., & Sterba, S.K. (2018). Ignoring a multilevel structure in mixture item response models: Impact on parameter recovery and model selection. Applied Psychological Measurement, 42, 136-154.
- Rights, J.D., Sterba, S.K., Cho, S-J., & Preacher, K.J. (2018). Addressing model uncertainty in item response theory person scores through model averaging. Behaviormetrika, 45, 495-503.
- Sterba, S.K. (2017). Pattern mixture models for quantifying missing-data uncertainty in longitudinal invariance testing. Structural Equation Modeling, 24, 283-300.
- Sterba, S.K. (2017). Partially nested designs in psychotherapy trials: A review of modeling developments. Psychotherapy Research, 27, 47-68.
- Sterba, S.K. & Rights, J.D. (2017). Effects of parceling on model selection: Parcel-allocation variability in model ranking. Psychological Methods, 22, 47-68.
- Gottfredson, N.C., Sterba, S.K. & Jackson, K.A. (2017). Explicating the conditions under which multilevel multiple imputation mitigates bias resulting from random coefficient-dependent missing longitudinal data. Prevention Science, 18, 12-19.
- Rights, J.D. & Sterba, S.K. (2016). The relationship between multilevel models and nonparametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity. British Journal of Mathematical and Statistical Psychology, 69, 316-343.
- Sterba, S.K., & Rights, J.D. (2016). Accounting for parcel-allocation variability in practice:Combining sources of uncertainty and choosing the number of allocations. Multivariate Behavioral Research, 51, 296-313.
- Sterba, S.K. (2016). A latent transition analysis model for latent-state-dependent nonignorable missingness. Psychometrika, 81, 506-534.
- Sterba, S.K. (2016). Interpreting and testing interactions in conditional mixture models. Applied Developmental Science, 20, 29-43.
- Sterba, S.K. (2016). Cautions on the use of multiple imputation when selecting between latent categorical versus continuous models for psychological constructs. Journal of Clinical Child and Adolescent Psychology, 45, 167-175.
- Sterba, S.K. & Gottfredson, N.C. (2015). Diagnosing global case influence on MAR versus MNAR model comparisons. Structural Equation Modeling, 22, 294-307.
- Lachowicz, M.J., Sterba, S.K. & Preacher, K.J. (2015). Investigating multilevel mediation with fully or partially nested data. Group Processes & Intergroup Relations, 18, 274-289.
- Sterba, S.K. (2014). Handling missing covariates in conditional mixture models under missing at random assumptions. Multivariate Behavioral Research, 49, 614-632.
- Sterba, S.K. (2014). Fitting nonlinear latent growth models with individually-varying time points. Structural Equation Modeling, 21, 630-647.
- Sterba, S.K., Preacher, K.J., Forehand, R., Hardcastle, E.J., Cole, D.A. & Compas, B.E. (2014). Structural equation modeling approaches for analyzing partially nested data. Multivariate Behavioral Research, 49, 93-118.
- Sterba, S.K., & Bauer, D.J. (2014). Predictions of individual change recovered with latent class or random coefficient growth models. Structural Equation Modeling, 21, 342-360.
- Sterba, S.K. (2013). Understanding linkages among mixture models. Multivariate Behavioral Research, 48, 775-815.
- Sterba, S.K. & Pek, J. (2012). Individual influence on model selection. Psychological Methods, 17, 582-599.
- Sterba, S.K., Baldasaro, R.E. & Bauer, D.J. (2012). Factors affecting the adequacy and preferability of semiparametric groups-based approximations of continuous growth trajectories. Multivariate Behavioral Research, 40, 590-634.
- Bauer, D.J. & Sterba, S.K. (2011). Fitting multilevel models with ordinal outcomes: Performance of alternative specifications and methods of estimation. Psychological Methods, 16, 373-390.
- Sterba, S.K. (2011). Implications of parcel-allocation variability for comparing fit of item-solutions and parcel-solutions. Structural Equation Modeling, 18, 554-577.
- Panter, A.T. & Sterba, S.K. (2011). Handbook of Ethics in Quantitative Methodology. Multivariate Applications Series. Taylor & Francis/Routledge.
- Sterba, S.K. & Bauer, D.J. (2010). Statistically evaluating person-oriented principles revisited: Reply to Molenaar (2010), von Eye (2010), Ialongo (2010) and Mun, Bates and Vaschillo (2010). Development & Psychopathology, 22, 287-294.
- Sterba, S.K. & Bauer, D.J. (2010). Matching method with theory in person-oriented developmental psychopathology research. Development & Psychopathology, 22, 239-254.
- Sterba, S.K. & MacCallum, R.C. (2010). Variability in parameter estimates and model fit across random allocations of items to parcels. Multivariate Behavioral Research, 45, 322-358.
- Sterba, S.K. Copeland, W., Egger, H., Costello, J., Erkanli, A. & Angold, A. (2010). Longitudinal dimensionality of adolescent psychopathology: Testing the differentiation hypothesis. Journal of Child Psychology and Psychiatry, 51, 871-884.
- Sterba, S.K. (2009). Alternative model-based and design-based frameworks for inference from samples to populations: From polarization to integration. Multivariate Behavioral Research, 44, 711-740.