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. This course will survey the advantages of modeling in randomized trials and will provide some guidance in developing a prospective statistical plan for use in a Phase III clinical trial. The methods covered in this course will apply to almost any regression model, including ordinary least squares, logistic regression models, and survival models. Statisticians and persons from other quantitative disciplines who are interested in multivariable regression analysis of univariate responses, in developing, validating, and graphically describing multivariable predictive models, and in covariable adjustment in randomized clinical trials.