- Breza, E., Chandrasekhar, A. G., McCormick, T. H., and Pan, M. (2019+) Using Aggregated Relational Data to feasibly identify network structure without network data (conditionally accepted,
*American Economic Review*). Li, Z. R., McCormick, T. H., and Clark, S. J. (2019+).Using Bayesian latent Gaussian graphical models to infer symptom associations in verbal autopsies. To appear,

*Bayesian Analysis*. codeGreen, A., McCormick, T. H., & Raftery, A. E. (2019+). Consistency for the tree bootstrap in respondent-driven sampling. To appear,

*Biometrika (Miscellanea)*. (pdf coming soon!)Li, Z. R., McCormick, T. H., and Clark, S. J. (2019). Bayesian Joint Spike-and-Slab Graphical Lasso. In

*Proceedings of the 35th International Conference on Machine Learning (ICML)*.Li, Z. R., & McCormick, T. H. (2019+). An Expectation Conditional Maximization approach for Gaussian graphical models. To appear,

*Journal of Computational and Graphical Statistics*. codeEadie, G., Huppenkothen, D., Springford, E., & McCormick, T. H. (2019+). Introducing Bayesian Analysis with m&m’s: an active-learning exercise for undergraduates. To appear,

*Journal of Statistics Education*. codeKunihama, T., Li, Z. R., Clark, S. J., & McCormick, T. H. (2019+). Bayesian factor models for probabilistic cause of death assessment with verbal autopsies. To appear,

*Annals of Applied Statistics*. codeWestling, T., & McCormick, T. H. (2019+). Beyond prediction: A framework for inference with variational approximations in mixture models. To appear,

*Journal of Computational and Graphical Statistics*. codeLi, Z. R., McCormick, T. H., & Clark, S. J. (2019+) Non-confirming Replication of ``Performance of InSilicoVA for Assigning Causes of Death to Verbal Autopsies: Multisite Validation Study using Clinical Diagnostic Gold Standards”, BMC Medicine 2018; 16:56. To appear,

*BMC Medicine.*Jha, P., Kumar, D., Dikshit, R., Budukh, A., Begum, R., Sati, P., Kolpak, P., Wen, R., Raithatha, S.J., Shah, U., Li, Z.R., Aleksandrowicz, L., Shah, P., Piyasena, K., McCormick, T. H., Gelband, H. & Clark, S. J. (2019) Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India.

*BMC Medicine*, 17, 116.Fosdick, B., McCormick, T. H., Murphy, T. B., Ng, T. L., and Westling, T. (2018). Multiresolution network models.

*Journal of Computational and Graphical Statistics*, 28, 185-196. code slidesCesare, N., Lee, H., McCormick, T. H., Spiro, E., and Zagheni, E. (2018). Promises and pitfalls of using digital traces for demographic research.

*Demography,*55, 1979-1999.Wang, F., McCormick, T. H., Rudin, C., and Gore, J. (2018+). Modeling recovery curves with application to Prostatectomy. To appear,

*Biostatistics.*codeLee, W., Fosdick, B., and McCormick, T. H. (2018). Inferring social structure from continuous-time interaction data. Discussion paper.

*Applied Stochastic Models in Business and Industry*, 34, 87-104. codeClark, S., Wakefield, J, McCormick, T. H., and Ross, M. (2018+). Hyak mortality monitoring system: Innovative sampling and estimation methods. To appear,

*Global Health, Epidemiology and Genomics*.Salter-Townshend, M. and McCormick, T. H. (2017). Latent space models for multiview network data.

*Annals of Applied Statistics*, 11: 1217-1244. codeBaraff, A., McCormick, T. H., and Raftery, A. E. (2016). Estimating Uncertainty in Respondent-Driven Sampling Using a Tree Bootstrap Method.

*Proceedings of the National Academy of Sciences (USA)*, 113: 14668-14673. R packageMcCormick, T. H., Li, Z., Calvert, C., Crampin, A. C., Kahn, K., and Clark, S. J. (2016). Probabilistic Cause-of-death Assignment using Verbal Autopsies.

*Journal of the American Statistical Association*, 111: 1036-1049. R packageArseniev-Koehler, A., Lee, H., McCormick, T. H., and Moreno, M. (2016). #Proana: Pro-Eating Disorder Socialization on Twitter.

*Journal of Adolescent Health*, 58: 659-664.McCormick, T. H. and Zheng, T. (2015). Latent surface models for networks using Aggregated Relational Data,

*Journal of the American Statistical Association*, 110:1684-1695. codeLetham, B., Rudin, C., McCormick, T. H., and Madigan, D. (2015). Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model.

*Annals of Applied Statistics*, 9:1350-1371. codeErtekin, S., Rudin, C, and McCormick, T. H. (2015). Predicting power failures with Reactive Point Processes.

*Annals of Applied Statistics*, 9: 122-144. codeMcCormick, T. H., Lee, H., Cesare, N., Shojaie, A., and Spiro, E. (2015). Using Twitter for Demographic and Social Science Research: Tools for Data Collection.

*Sociological Methods and Research*, 1-32.Lee, H., McCormick, T. H., Wildeman, C., and Hicken, M. (2015). Racial inequalities in connectedness to imprisoned individuals in the United States.

*Du Bois Review: Social Science Research on Race*, 12: 269-282.Maltiel, R., Raftery, A., McCormick, T. H., and Baraff, A. (2015). Estimating Population Size Using the Network Scale Up Method.

*Annals of Applied Statistics*, 9:1247-1277. R packageWestling, T., and McCormick, T. H. (2014). Sandwich Covariance Estimation for Variational Inference.

*NIPS Workshop on Advances in Variational Inference.*codeMcParland, D., Gormley, I. C., McCormick, T. H., Clark, S. J., Kabudula, C., and Collison, M. (2014). Clustering South African households based on their asset status using latent variable models.

*Annals of Applied Statistics*, 8: 747-776. codeMcCormick, T. H., Ferrell, R., Karr, A., and Ryan, P. B. (2014). Knowledge Discovery in Output from Large-Scale Medical Analytics.

*Statistical Learning & Data Mining*, 7:404-412.Rudin, C., Ertekin, S., Passonneau, R., Radeva, A., Tomar, A., Xie, B., Lewis, S., Riddle, M., Pangsrivinij, D, and McCormick, T. H. (2014). Analytics for Power Grid Distribution Reliability in New York City.

*Interfaces*, 44: 364-383.Young, W., Blumenstock J. E., Fox, E. B., and McCormick, T. H. (2014). Detecting and classifying anomalous behavior in spatiotemporal network data.

*The 20th ACM Conference on Knowledge Discovery and Mining (KDD ‘14), Workshop on Data Science for Social Good*, New York, NY.McCormick, T. H., and Zheng, T. (2013). Network-based methods for accessing hard-to-reach populations using standard surveys. In

*Hard-to-Survey Populations*. Editors K. Wolter and R. Tourangeau.McCormick, T. H., Ruf, J., Moussa, A., Diprete, T. D., Gelman, A., Teitler, J., and Zheng, T. (2013). A practical guide to measuring social structure using indirectly observed network data.

*Journal of Statistical Theory and Practice*, 7:120-132.McCormick, T. H., and Zheng, T. (2012). Latent demographic profile estimation in at-risk populations.

*Annals of Applied Statistics*, 6: 1795-1813.McCormick, T. H., Rudin, C., and Madigan, D. (2012). A hierarchical model for association rule mining of sequential events: an approach to automated medical symptom prediction.

*Annals of Applied Statistics*, 6: 652-668.McCormick, T. H., He, R., Kolaczyk, E., and Zheng, T. (2012). Surveying hard-to-reach groups through sampled respondents in a social network: A comparison of two survey strategies.

*Statistics in Biosciences*, 4: 177-195.Diprete, T. D., Gelman, A., McCormick, T. H., Teitler, J., and Zheng, T. (2011). Segregation in social networks based on acquaintanceship and trust.

*American Journal of Sociology*, 116, 1234-83.McCormick, T. H., Raftery, A. E., Madigan, D., and Burd, R. (2011). Dynamic logistic regression and dynamic model averaging for binary classification.

*Biometrics*, 68, 23-30. R packageMcCormick, T. H. (2011). Bayesian analysis of social network data.

*ISBA Bulletin*, 18, 6-9.McCormick, T. H., Salganik, M. J. and Zheng, T. (2010). How many people do you know?:Efficiently estimating personal network size.

*Journal of the American Statistical Association,*105, 59-70.McCormick, T. H. and Zheng, T. (2010). A latent space representation of overdispersed relative propensity in ‘How many X’s do you know?’ data. in

*Conference Proceedings of the Joint Statistical Meetings*, Vancouver, B.C.McCormick, T. H. and Zheng, T. (2009). Towards a unified framework for inference in Aggregated Relational Data in

*Conference Proceedings of the Joint Statistical Meetings*, Washington, D.C.McCormick, T. H., Ruf, J., Moussa, A., Diprete, T. D., Gelman, A., Teitler, J., and Zheng, T. (2009). Measuring social distance using indirectly observed network data. in

*Conference Proceedings of the Joint Statistical Meetings*, Washington, D.C.McCormick, T. H. and Zheng, T. (2007). Adjusting for recall bias in ‘How many X’s do you know?’ surveys. in

*Conference Proceedings of the Joint Statistical Meetings*, Salt Lake City, Utah.