2. Models for Cross-Sectional Data.
3. Univariate U-Statistics.
4. Models for Clustered Data.
5. Multivariate U-Statistics.
6. Functional response Models.
- The level of accessibility and the variety of timely applications that demonstrate the utility and power of the hybrid inference paradigm are unique to this volume.
- The scope of applications of the U-Statistics theory is more broadly defined than seen in other books. Emphasis is placed on nonparametric applications when and where appropriate.
- The large number of motivating examples and real study applications in genetics, sequencing data, cDNA, protein arrays, biomedical and psychological research, as well as the concrete steps needed to apply the theory to practical problems, serves to strengthen the utility and comprehension of the book.
- The use of case studies throughout the book underscores the real-life nature of the content.
- The unusual inclusion of certain topics such as repeated measurements and clustered data make the book timely and modern.
- The appendix of the book and a soon-to-be posted .ftp site provide several computer codes for producing the results that are discussed in the book.