INVITED PRESENTATIONS & LECTURES

  • Tong, X. (2024, November). Investigating Small Subpopulations using a Robust Growth Mixture Modeling Approach. An invited talk presented at the Methods & Statistics speaker series at Michigan State University, MI.

  • Tong, X., & Depaoli, S. (2024, July). Revisiting Bayesian Two Sample Inference. An invited presentation at the International Society for Data Science and Analytics annual meeting. Vienna, Austria.

  • Tong, X. (2024, June). Bayesian Longitudinal Data Modeling using Conditional Quantiles. An invited talk presented to the School of Sciences, Xi’an Polytechnic University, China.

  • Tong, X. (2024, February). Bayesian Compositional Data Analysis and Variable Selection. An invited talk given to the Quant Methods colloquium series at Vanderbilt University, TN.

  • Tong, X. (2023, July). Bayesian Longitudinal Data Modeling. An invited 3-hour workshop given at the preconference of the 2023 annual meeting of the International Society for Data Science and Analytics. Shanghai, China.

  • Tong, X., (2022, February). Bayesian Analysis of Longitudinal Data using Conditional Quantiles. An invited Zoom talk given to the Quantitative Psychology and Modeling Program at McGill University, Canada.

  • Tong, X., (2021, December). R Workshop. An invited 3-hour workshop given at the preconference of Pacific Rim Objective Measurement Symposium 2021.

  • Tong, X., (2021, November). Robust Bayesian Growth Curve Modeling using Conditional Quantiles. An invited talk given at the QC seminar series. Charlottesville, VA.

  • Tong, X. (2021, July). Robust Bayesian Analysis of Longitudinal Data. Virtual forum on Data Science and Methodology.

  • Tong, X., (2020, December). Conditional Median based Bayesian Growth Mixture Modeling. An invited virtual talk given to the Department of Psychology, UCLA.

  • Tong, X. (2020, March). Robust Bayesian Growth Curve Modeling using Conditional Medians. Given at the 2020 Charlottesville Women in Data Science Conference. Charlottesville, VA.

  • Tong, X. (2019, November). Bayesian Statistics. An invited 3-hour Bayesian workshop given to graduate students at the Max Planck Institute.

  • Tong, X., Ke, Z., & *Sjobeck, G. (2018, June). Robust Semiparametric Bayesian Methods in Growth Curve Modeling with Nonnormal Missing Data. An invited talk given at the 2nd International Conference on Econometrics and Statistics (Invited Paper Session). Hong Kong, China.

  • Tong, X. (2017, Feburary). How to Handle Outlying Observations in Structural Equation Modeling: Deletion or Robust Methods? An invited talk given to the Department of Biostatistics, Virginia Commonweath University, Richmond, VA.

  • Tong, X. (2016, December). Strategies for Nonnormal Data Analysis in Growth Curve Modeling. An invited talk at the Silk Road Young Scholars Forum, Xi’an, China.

  • Tong, X. (2016, June). Robust Frequentist versus Bayesian Methods for Growth Curve Modeling. An invited talk given to the Department of Mathematics, Renmin University of China, Beijing, China.

  • Tong, X. (2016, June). Diagnostics of Growth Curve Modeling. An invited talk given to the Department of Psychology, Sun Yat-Sen University, Guangzhou, China.

  • Tong, X. (2013, June). Robust structural equation modeling with nonnormal/missing data. An invited talk given to the Department of Mathematics, Renmin University of China, Beijing, China.

  • Yuan, K.-H., Tong, X., & Zhang, Z. (2012, July). Bias and efficiency for SEM with missing data and auxiliary variables: Robust method versus normal distribution based ML. Given at the 2nd Institute of Mathematical Statistics Asia Pacific Rim Meeting (Invited Paper Session). Tsukuba, Japan.

REFEREED CONFERENCE PRESENTATIONS

  • Dettmer, A. M., Simon, C., Topping, N., Tong, X., & Lillard, A. S. (2024, October). Chronic Hypothalamic-pituitary-adrenal (HPA) Axis Activity in School Children as a Function of
    Educational Setting. An oral presentation at the 2024 International Society for Developmental Psychobiology. Chicago, IL.

  • Tong, X. (2024, October). Value of Small: Investigating Small Subpopulations using a Robust Growth Mixture Modeling Approach. A lecture presented at the 2024 LIFE Academy. Berlin, Germany.

  • Tong, X., & *Tang, D. (2024, August). Bayesian Variable Selection with Compositional Data. An oral presentation at the 2024 Annual Conference of American Psychological Association. Seattle, WA.

  • Tong, X., & *Tang, D. (2024, July). Quantile Longitudinal Data Modeling with Missing Data. An oral presentation at the 2024 Annual Conference of Psychometric Society. Prague, Czech Republic.

  • Eberle, J. W., Daniel, K. E., Baee, S., Silverman, A. L., Lewis, E., Baglione, A. N., Werntz, A., French, N. J., Ji, J. L., Hohensee, N., Tong, X., Huband, J. M., Boukhechba, M., Funk, D. H., Barnes, L. E., & Teachman, B. A. (2024, November). Web-based interpretation bias training to reduce anxiety: A sequential multiple-assignment randomized trial. In Wolfe, E. C., & Teachman, B. A. (Chairs), Increasing access to care: Implementing evidence-based mental health interventions through community partnerships and non-specialist providers [Symposium]. Meeting of the Association for Behavioral and Cognitive Therapies, Philadelphia, PA, United States. https://bit.ly/3TiDAMc.

  • Tong, X., & Meyer, M. J. (2024, February). Introducint Bayesian statistics to undergraduate students with classroom games. A teaching demo given at the Southeastern Teaching of Psychology Conference. Atlanta, GA.

  • Tong, X. (2023, October). Bayesian Compositional Data Analysis. Oral presentation at the 2023 Annual Society of Multivariate Experimental Psychology. Iowa City, IA.

  • *Tang, D., & Tong, X. (2023, July). An investigation of missing data analytical methods in longitudinal research: Traditional and machine learning approaches. Oral presentation at the 2023 Annual Conference of Psychometric Society. College Park, MD.

  • Tong, X., *Di, J., & *Liu, Y. (2023, July). Bayesian Compositional Data Analysis with Informative Priors. Oral presentation at the 2023 meeting of the International Society for Data Science and Analytics. Shanghai, China.

  • Tong, X., Liu, H., *Tsang, S., & Wood, A. (2023, July). An analysis of emotion contagion with longitudinal text data.        Oral presentation at the 2023 meeting of the International Society for Data Science and Analytics. Shanghai, China.

  • *Eberle, J. W., *Daniel, K. E., Baee, S., Behan, H. C., Silverman, A. L., Baglione, A. N., Werntz, A., French, N. J., Ji, J. L., Hohensee, N., Tong, X., Huband, J. M., Boukhechba, M., Funk, D. H., Barnes, L. E., & Teachman, B. A. (2023, June 20-21). Web-based interpretation bias training to reduce anxiety: A sequential multiple-assignment randomized trial [Flash talk]. Meeting of the Society for Digital Mental Health. https://bit.ly/3yCMedA

  • *Li, Y., & Tong, X. (2023, May). Inconsistency between conventional levels of different effect size measures: Practical suggestions for sample size planning.   Poster presentation at the 2023 Association for Psychological Science Annual Convention. Washington, D.C.

  • Lillard, A. S., Tong, X., & Bray, P. M. (2023, April). Racial and Ethnic Parity in Preschool: Public Montessori Versus Lottery Wait List Alternatives.          Oral presentation at the 2023 American Educational Research Association meeting. Chicago, IL.

  • Tong, X., & Liu, H. (2023, January). Robust Data Analysis in Education Research. Oral presentation at the 2023 meeting of the Hawaii International Conference on Education. Honolulu, HI.

  • Tong, X. (2022, June). Robust Bayesian Analysis of Longitudinal Data using Conditional Quantiles. Oral presentation at the 2022 meeting of the International Society for Data Science and Analytics. Notre Dame, IN.

  • Tong, X., & Kim, S. (2022, May). Robust Bayesian Growth Curve Modeling using Conditional Quantiles. Oral presentation at the 2022 Association for Psychological Science Annual Convention. Chicago, IL.

  • Snyder, A. L., Tong, X., & Lillard, A. S. (2022, April). Standardized Test Proficiency in Public Montessori Schools. Oral presentation at the 2022 American Educational Research Association Annual Meeting. San Diego, CA.

  • Meyer, M. J., Schmidt, K. M., & Tong, X. (2022, February). Using the R Packages Rmarkdown and Learnr for Creating Interactive Websites to Teach Statistical Analyses to Psychology Students. A (virtual) teaching tutorial given at the Southeastern Teaching of Psychology Conference.

  • Tong, X., *Kim, S., & Ke, Z. (2021, July). The Impact of Likelihoods and Outliers on Bayesian Model Selection. Oral presentation at the 2021 (virtual) International Meeting of the Psychometric Society.

  • Snyder, A. L., Tong, X., & Lillard, A. S. (2021, April). Standardized Test Performance of Hispanic, Black, and Low Income Students in Public Montessori Schools. Oral presentation at the 4th Annual Diversifying Scholarship Research Conference at the University of Virginia.

  • *Womack, S., Wilson, M., Tong, X., Lemery-Chalfant, K., & Shaw, D. (2021, April). Trajectories of Early Childhood Environmental Instability and the Development of Disruptive Behaviors into Adolescence: A Prospective Study of At-Risk Families. Poster presented at the 2021 (virtual) Society for Research in Child Development Biennial Meeting.

  • Schmidt, K. M., Tong X., & Meyer, M, J., (2021, February). Using R Shiny Apps to Illustrate Statistical Concepts with Psychology Courses. A teaching demonstration at the (virtual) Southeastern Teaching of Psychology Conference.

  • *Mazen, J., & Tong, X. (2020, October). Bias Correction for Replacement Samples in Longitudinal Research.     Poster presented at the 2020 (virtual) Society of Multivariate Experimental Psychology Meeting.

  • *Kim, S., & Tong, X. (2020, July). Bayesian Growth Mixture Modeling using Conditional Medians.  Paper presented at the 2020 (virtual) International Meeting of the Psychometric Society.

  • *Zhang, T., Tong, X., & Zhou, J. (2020, May). Robust Bayesian Growth Curve Modeling using Double Conditional Medians.        Paper presented at the (virtual) 2020 meeting of the International Society for Data Science and Analytics.

  • *Shi, D. & Tong, X. (2019, May). Eliminating selection bias in two-stage Bayesian causal models with nonnormal missing data.  Paper presented at the 31th Annual Convention of Association for Psychological Science, Washington, D. C.

  • *Moulder, R. G. & Tong, X. (2019, May). Testing for interindividual differences in intraindividual change in Bayesian growth curve modeling.  Paper presented at the 31th Annual Convention of Association for Psychological Science, Washington, D.C.

  • Tong, X., *Zhang, T., & Zhou, J. (2019, May). Robust Growth Curve Modeling using Conditional Medians.  Poster presented at the 31th Annual Convention of Association for Psychological Science, Washington, D. C.

  • *Womack, S., Wilson, M., Tong, X., Shaw, D., & Lemery-Chalfant, K. (2019, March). Longitudinal Associations Between Family Instability and Conduct Problems in Early Childhood. Poster presented at the 2019 Society for Research in Child Development Biennial Meeting, Baltimore, MD.

  • *Mazen, J. A. M. & Tong, X. (2018, October). Bias Correction for Replacement Samples in Longitudinal Research. Poster presented at the Fall 2018 Academy of the International Max Planck Research School on the Life Course, Charlottesville, VA.

  • *Mazen, J. A. M., & Tong, X., (2018, September). Bias Correction for Replacement Samples in Longitudinal Research.  Paper presented at the 2018 Developmental Methods Conference, Whitefish, MT.

  • Tong, X., *Zhang, T., & Zhou, J. (2018, July). Robust and Interpretable Quantile Growth Curve Modeling. Paper presented at the 2018 International Forum on Statistics at Renmin University of China, Beijing, China.

  • *Shi, D. & Tong, X. (2017, October). Bayesian Robust Two-stage Causal Modeling with Nonnormal Missing Data. Poster presented at the 2017 Annual Society of Multivariate Experimental Psychology Meeting, Minneapolis, MN.

  • Tong, X. (2017, July). How to Handle Outlying Observations in SEM: Deletion or Robust Methods? Paper presented at the 2017 Annual Conference of Psychometric Society, Zurich, Switzerland.

  • *Kim, B. & Tong, X. (2017, May). What to Do with Outliers in Bayesian Analysis.  Poster presented at the 29th Annual Convention of Association for Psychological Science, Boston, MA.

  • *Mazen, J. A. M. & Tong, X. (2017, May). Evaluation of supplemental samples in longitudinal research with nonnormal missing data.  Paper presented at the 2017 Modern Modeling Methods Conference, Storrs, CT.

  • Lillard, A. S., Heise, M. J., Richey, E., Tong, X., Bray, P., Hart, A. (2017, April). Outcomes in Montessori and Conventional Preschool Programs. Poster presented at the 2017 Society for Research in Child Development Biennial Meeting, Austin, TX.

  • *Moulder, R. G. & Tong, X. (2017, May). Overcoming the Boundary Problem in Bayesian Growth Curve Modeling: A Data Permutation Method for Testing Random Slopes.  Poster presented at the 2017 Modern Modeling Methods Conference, Storrs, CT.

  • Tong, X. & Boker, S. M. (2016, August). The Impact of Masking and Swamping Effects for Multivariate Outlier Diagnosis in Structural Equation Modeling.  Paper presented at the 2016 Annual Convention of the American Psychological Association, Denver, CO.

  • Ke, Z., & Zhang, Q., & Tong, X. (2016, August). Random Effect Meta-Analytic Structural Equation Modeling: A Bayesian Approach.  Paper presented at the 2016 Annual Convention of the American Psychological Association, Denver, CO.

  • *Shi, D. & Tong, X. (2016, August). The Impact of Prior Information on Bayesian Estimation for Latent Basis Growth Models.  Paper presented at the 2016 Annual Convention of the American Psychological Association, Denver, CO.

  • Tong, X., & Boker, S. M. (2016, May). Bootstrap Standard Error Estimates in Latent Differential Equation Modeling. Paper presented at the 28th Annual Convention of Association for Psychological Science, Chicago, IL.

  • *Shi, D. & Tong, X. (2016, April). The Impact of Informative Priors for Parameter Recovery in Bayesian Confirmatory Factor Model. Paper presented at the 2016 Annual Meeting of American Educational Research Association, Washington, DC.

  • Tong, X., & Ke, Z. (2015, July). Growth curve modeling for nonnormal data: a two-stage robust approach versus a semiparametric Bayesian approach.  Paper presented at the 2015 Annual Conference of Psychometric Society, Beijing, China.

  • Tong, X., & Zhang, Z. (2015, May). Robust Bayesian Methods in Growth Curve Modeling.  Paper presented at the 2015 Modern Modeling Methods Conference, Storrs, CT.

  • Taylor, L. K., Tong, X., & Maxwell, S. E. (2014, September). Evaluating supplemental samples in longitudinal research: Replacement and Refreshment approaches. Poster presentation at the 2014 Society for Research on Child Development, Special topic Meeting on Developmental Methodology, San Diego, CA.

  • Tong, X., & Zhang, Z. (2014, May). Robust semiparametric Bayesian methods in growth curve modeling with nonnormal data.  Paper presented at the 26th Annual Convention of Association for Psychological Science, San Francisco, CA.

  • Seroczynski, A.D., Tong, X., Grundy, A., Jobst, A., and Hull, B. (2014, January). Quantifying the Qualitative: Using Growth Curve Models to Differentiate Moral Development among Juvenile Offenders.  Paper presented at the 2nd Annual Conference of the Jubilee Centre for Character and Values, Oxford, UK.

  • Tong, X., & Zhang, Z. (2013, October). Nonparametric Bayesian modeling with applications in growth curve analysis.  Poster presentation at the 11th Graduate Student Pre-conference of Annual Society of Multivariate Experimental Psychology Meeting, Tampa, FL.

  • Tong, X., & Zhang, Z. (2013, July). Outlying Observation Diagnostics in Growth Curve Modeling.  Paper presented at the 78th Annual Conference of Psychometric Society, Arnhem, the Netherlands.

  • Tong, X., Zhang, Z., & Yuan, K.-H. (2012, May). Evaluation of test statistics for robust structural equation modeling.  Paper presented at the 24th Annual Convention of Association for Psychological Science, Chicago, IL.

  • Zhang, Z., Lai, K., Lu, Z., & Tong, X. (2012, May). Bayesian Robust Growth Curve Modeling Based on Student's t Distribution.  Paper presented at the 24th Annual Convention of Association for Psychological Science, Chicago IL.

  • Tong, X., Zhang, Z., & Yuan, K.-H. (2011, October). Evaluation of test statistics for robust SEM with non-normal missing data.  Paper presented at the 9th Graduate Student Pre-conference of Annual Society of Multivariate Experimental Psychology Meeting, Norman, OK.

  • Tong, X., & Zhang, Z. (2011, August). Bayesian inference for robust growth curve modeling using t distribution.  Paper presented at the 119th Convention of the American Psychological Association, Washington, DC.

  • Cheung, R. Y. M., Tong, X., & Shrestha, G. (2011, June). The role of social support in the relationship between family violence and suicidal tendency: a test of competing hypotheses. Paper presented at the Society of Prevention Research 2011 Annual Meeting, Washington, DC.