Time: 4/29/2016, 1:30-2:50pm
Place: Geno Cafe (Room E3609)
Speaker: Joanna Shih, Biometric Research Branch, Division of Cancer Treatment and Diagnosis, NCI, NIH
Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to $U$-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods were applied to two data sets collected from MRI imaging studies for illustration.
5/6/2016 Zhenke Wu, Department of Biostatistics, JHU
5/13/2016 Fang Han, Department of Biostatistics, JHU
5/20/2016 Takumi Saegusa, Department of Mathematics, University of Maryland, College Park. Short Course: ``Empirical Processes''
5/27/2016 Takumi Saegusa, Department of Mathematics, University of Maryland, College Park. Short Course: ``Empirical Processes''
6/3/2016 Jon Steingrimsson, Department of Biostatistics, JHU. Short Course: ``Survival Trees and Forests''
6/10/2016 Jon Steingrimsson, Department of Biostatistics, JHU. Short Course: ``Survival Trees and Forests''
9/2/2016 Rajeshwari Sundaram, Biostatistics and Bioinformatics
Branch, NICHD, NIH
9/30/2016 Qing Pan, Department of Statistics, George Washington University