1. Why we (usually) don't have to worry about multiple comparisons Gelman, Andrew E.; Hill, Jennifer; Yajima, Masanao 2009 Articles StatisticsBayesian statistical decision theoryMultilevel models (Statistics)Statistical hypothesis testing
2. Why we (usually) don't have to worry about multiple comparisons Gelman, Andrew E.; Hill, Jennifer; Yajima, Masanao 2009 Presentations (Communicative Events) Statistics
3. Why we (usually) don't have to worry about multiple comparisons Gelman, Andrew E.; Hill, Jennifer; Yajima, Masanao 2007 Presentations (Communicative Events) Statistics
4. When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts? Donoho, David L.; Stodden, Victoria C. 2004 Articles Statistics
5. What will we know on Tuesday at 7pm? Gelman, Andrew E.; Silver, Nate 2008 Articles Political scienceStatistics
6. What does "Do campaigns matter?" mean? Bafumi, Joseph; Gelman, Andrew E.; Park, David K. 2004 Articles Political scienceStatisticsPresidents--Election
7. Unbiased Penetrance Estimates with Unknown Ascertainment Strategies Gore, Kristen 2014 Theses Statistics
8. Tree-Based Integration of One-versus-Some (OVS) Classifiers for Multiclass Classification Ding, Yuejing; Zheng, Tian 2006 Reports Statistics
9. Toward a scalable Bayesian workflow Yao, Yuling 2021 Theses StatisticsBayesian statistical decision theoryBayesian statistical decision theory--Mathematical models
10. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology Sahai, Swupnil 2018 Theses StatisticsAstronomySociologyBayesian statistical decision theoryMultilevel models (Statistics)
11. Time Series Modeling with Shape Constraints Zhang, Jing 2017 Theses StatisticsTime-series analysis--Mathematical models
12. Thoughts on new statistical procedures for age-period-cohort analyses Gelman, Andrew E. 2008 Articles Statistics
13. The Prior Can Often Only Be Understood in the Context of the Likelihood Gelman, Andrew E.; Simpson, Daniel; Betancourt, Michael Joseph 2017 Articles Bayesian statistical decision theoryDistribution (Probability theory)Statistics
14. The playing field shifts: Predicting the seats-votes curve in the 2008 U.S. House election Kastellec, Jonathan P.; Gelman, Andrew E.; Chandler, Jamie P. 2008 Articles Political scienceMathematical statisticsStatistics
15. Surveying Hard-to-Reach Groups Through Sampled Respondents in a Social Network McCormick, Tyler H.; Zheng, Tian; He, Ran; Kolaczyk, Eric 2012 Articles StatisticsSocial sciences--Research
16. Struggles with survey weighting and regression modeling Gelman, Andrew E. 2007 Articles Political scienceMathematical statisticsStatistics
17. Stochastic Differential Equations and Strict Local Martingales Qiu, Lisha 2018 Theses StatisticsMathematicsStochastic differential equationsMartingales (Mathematics)Convergence
18. Statistical Perspectives on Modern Network Embedding Methods Davison, Andrew 2022 Theses StatisticsMachine learning--Statistical methodsMachine learning--Graphic methodsComputer networks
19. Statistical methods for indirectly observed network data McCormick, Tyler H. 2011 Theses Statistics
20. Statistical Machine Learning Methods for the Large Scale Analysis of Neural Data Mena, Gonzalo Esteban 2018 Theses StatisticsMachine learningNeural circuitry--Data processingNeurotechnology (Bioengineering)