Statisticians who want to learn how to graphically present complex regression models to non-statisticians. Analysts who would like to learn how to incorporate multiple imputation with regression models to handle missing and incomplete data. Biostatisticians, health services and outcomes researchers, and economists who need to study or predict health outcomes or resource utilization. Then a default overall modeling strategy will be described. Then the freely available S-Plus Design library will be overviewed.
Design facilitates most of the steps of the modeling process.
Next, statistical methods related to binary logistic models will be covered. In the hands-on computer lab students will develop, validate, and graphically describe multivariable regression models themselves. The methods covered in this course will apply to almost any regression model, including ordinary least squares, logistic regression models, and survival models. He received his Ph.D. in biostatistics from the University of North Carolina, Chapel Hill in 1979, where he studied under P.K. Sen. Dr. Harrell has been involved in statistical computing since 1969 and is the author of many S-Plus functions and SAS procedures. Since 1973 he has been involved in medical applications of statistics, especially in the area of survival analysis and clinical prediction modeling.