Most Popular Articles in the The University of North Carolina at Chapel Hill Department of Biostatistics Technical Report Series*

  1. Testing random effects in the linear mixed model using approximate Bayes factors, Benjamin R. Saville and Amy H. Herring
    Summary Download PDF [1.1 MB]
  2. Analyzing Correlated Longitudinal and Survival Data in Clinical Trials Using Multivariate Time-to-Event Methods, Benjamin R. Saville, Amy H. Herring, and Gary G. Koch
    Summary Download PDF [1.3 MB]
  3. Reinforcement Learning Design for Cancer Clinical Trials, Yufan Zhao, Michael R. Kosorok, and Donglin Zeng
    Summary Download PDF [1.1 MB]
  4. Graphical Displays for Clarifying How Allocation Ratio Affects Total Sample Size for the Two Sample Logrank Test, Benjamin R. Saville, Yong S. Kim, and Gary G. Koch
    Summary Download PDF [583 K]
  5. Regression Models for Identifying Noise Sources in Magnetic Resonance Images, Hongtu Zhu, Yimei Li, Joseph G. Ibrahim, Xiaoyan Shi, Hongyu An, Yasheng Chen, Weili Lin, Daniel B. Rowe, and Bradley G. Peterson
    Summary Download PDF [7.6 MB]
  6. Variable Selection by Bayesian Adaptive Lasso and Iterative Adaptive Lasso, with Application for Genome-wide Multiple Loci Mapping, Wei Sun, Joseph G. Ibrahim, and Fei Zou
    Summary Download PDF [1.7 MB]
  7. Testing Variance Components in Multilevel Linear Models using Approximate Bayes Factors, Benjamin R. Saville, Amy H. Herring, Jay S. Kaufman, and David A. Savitz
    Summary Download PDF [1.3 MB]
  8. Reinforcement Learning Strategies for Clincal Trials in Non-small Cell Lung Cancer, Yufan Zhao, Michael R. Kosorok, Donglin Zeng, and Mark A. Socinski
    Summary Download PDF [1.1 MB]
  9. Performance of One-Step Approximation Relative to Exact Cluster Cook's Distance for GEE, John Preisser, Kunthel By, and Bahjat Qaqish
    Summary Download PDF [503 K]
  10. On Asymptotically Optimal Tests Under Loss of Identifiability in Semiparametric Models, Rui Song, Michael R. Kosorok, and Jason P. Fine
    Summary Download PDF [1.5 MB]

* Based on the average number of full-text downloads per day since the paper was posted. Updated as of 11/10/09.