Usage of S-PLUS for more advanced statistical methods such as simulation and bootstrapping is surveyed. Then major emphasis is given to table making and S-PLUS and Hmisc graphical functions useful in everyday exploratory work and to present final summary statistics. The course concludes with discussion of some tools for making analyses reproducible, an important facit for regulatory and other scientific review of final results. Then a default overall modeling strategy will be described. Then the public domain S-Plus Design library will be overviewed.
Design facilitates most of the steps of the modeling process.
Next, statistical methods related to binary and ordinal logistic and survival models will be covered. In the hands-on computer lab, students will develop, validate, and graphically describe multivariable regression models themselves. The course includes both lecture and hands-on instruction, with each student using a PC to implement examples and exercises.