Module dates/times: Wednesday, July 11, 1:30-5 p.m.; Thursday, July 12, 8:30 a.m.-5 p.m., and Friday, July 13, 8:30 a.m.-5 p.m.
This module will introduce linear regression as a tool for studying relationships between continuous outcomes and continuous, binary, and categorical predictors. Using linear regression as the foundation, we will explore other regression methods, including logistic regression for the analysis of binary outcomes. Specific topics discussed are: linear regression; regression diagnostics; ANOVA; multiple comparisons; logistic regression; generalized linear models. Participants will have the opportunity for hands-on experience, using R. This module is designed as a foundation for the quantitative genetics and association mapping modules. It assumes the material in Module 1 and will cover the basic commands in R.
Rebecca Hubbard is Associate Professor of Biostatistics at the University of Pennsylvania. Her research focuses on development and application of statistical methodology for studies that use observational data from clinical medical practice. Her work emphasizes development of statistical tools for biomedical inference and has been applied to studies of cancer screening, aging and dementia, pharmacoepidemiology, women’s health and behavioral health. Her most recent publication is “An electronic health record-based algorithm to ascertain the date of second breast cancer events,” Medical Care 55:E91-E87.
Mary Lou Thompson is Professor of Biostatistics at the University of Washington. She works on epidemiology, longitudinal data, diagnostic methods, maternal and child health, occupational health, aging and cognition. Her most recent publication is “Cognitive trajectory changes over 20 years before dementia diagnosis: A large cohort study.” J American Geriatrics Society 65:2627-2633.