#### Current technical reports and working papers

- Bayesian Joint Spike-and-Slab Graphical Lasso (with Z. R. Li and S. Clark). 2018. pdf
- Quantifying the Contributions of Training Data and Algorithm Logic to the Performance of Automated Cause-assignment Algorithms for Verbal Autopsy (with Z. R. Li and S. Clark). 2018. pdf
- Bayesian factor models for probabilistic cause of death assessment with verbal autopsies (with T. Kunihama, Z. R. Li and S. Clark). 2018. pdf code
- Bayesian latent Gaussian graphical models for mixed data with marginal prior information (with Z. R. Li and S. Clark). 2017. pdf code
- An Expectation Conditional Maximization approach for Gaussian graphical models (with Z. R. Li). 2017. pdf code
- Using Aggregated Relational Data to feasibly identify network structure without network data (with E. Breza, A. Chandrasekhar and M. Pan). 2017. pdf
- Standard errors for regression on relational data with exchangeable errors (with B. Fosdick and F. Marrs). 2017. pdf code R package
- Consistency, Calibration, and Efficiency of Variational Inference (with T. Westling). 2017. pdf code
- Examining Racial Segregation in Associative Networks on Twitter (with N. Cesare, E. Spiro, and H. Lee). 2017. pdf
- Migrants, information, and working conditions in Bangladeshi garment factories (with L. Boudreau and R. Heath). 2016. pdf
- Online Information Behaviors During Disaster Events: Roles, Routines, and Reactions (with E. Spiro and H. Reeder). 2014. pdf
- Improving attribute prediction through Network-Augmented Prediction (with A. Zimmerman, H. Lee, and A. Shojaie). 2013. pdf

#### Published papers

- Fosdick, B., McCormick, T. H., Murphy, T. B., Ng, T. L., and Westling, T. (2018+) Multiresolution network models. To appear,
*Journal of Computational and Graphical Statistics.*pdf slides code - Cesare, N., Lee, H., McCormick, T. H., Spiro, E., and Zagheni, E. (2018+) Promises and pitfalls of using digital traces for demographic research. To appear,
*Demography.*pdf - Wang, F., McCormick, T. H., Rudin, C., and Gore, J. (2018+) Modeling recovery curves with application to Prostatectomy. To appear,
*Biostatistics.*pdf code - Lee, W., Fosdick, B., and McCormick, T. H. (2018+) Inferring social structure from continuous-time interaction data. Discussion paper. To appear,
*Applied Stochastic Models in Business and Industry*. pdf code - Clark, 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*. pdf - Salter-Townshend, M. and McCormick, T. H. (2017) Latent space models for multiview network data.
*Annals of Applied Statistics*, 11: 1217-1244. pdf supplement/code - Baraff, 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. pdf software - McCormick, 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. pdf supplementary material software - Arseniev-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. pdf -
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. pdf - Letham, 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. pdf supplement/code - Ertekin, S., Rudin, C, and McCormick, T. H. (2015). Predicting power failures with Reactive Point Processes.
*Annals of Applied Statistics*, 9: 122-144. pdf supplement/replication materials - McCormick, 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. pdf - 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. pdf - 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. pdf software -
Westling, T., and McCormick, T. H. (2014) Sandwich Covariance Estimation for Variational
Inference.
*NIPS Workshop on Advances in Variational Inference.*pdf code -
McParland, 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. pdf supplement/code - McCormick, 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. pdf - 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. pdf - 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. pdf - 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. pdf - McCormick, T. H., and Zheng, T. (2012) Latent demographic profile estimation in at-risk populations.
*Annals of Applied Statistics*, 6: 1795-1813. pdf - 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. pdf - 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. pdf - 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. pdf - 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. pdf - McCormick, T. H. (2011). Bayesian analysis of social network data.
*ISBA Bulletin*, 18, 6-9. pdf -
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. pdf -
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. pdf -
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. pdf -
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. pdf -
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. pdf