R統計回歸模式於環境流行病學之應用

For each session, a 2-hour lecture will be delivered followed by a 1-hour hands-on analysis using R statistical program. Students will be able to implement their own codes for statistical analysis taught in the class.

1. Use R program for statistical analysis and apply frequently used statistical models on their own research, 2. Learn how to model continuous exposures and outcomes in an advanced fashion (e.g. splines, polynomial regression), 3. Handle with the correlated data in the setting of environmental epidemiology, 4. Deal with data when the underlying statistical assumptions do no hold, 5. Apply state-of-art models in epidemiological studies

60% Final project (a real-world dataset will be distributed for analysis) 20% Two homework assignments (10% for each) 20% Class Participation

Course Text Books:  Peter Dalgaard. Introductory Statistics with R (Paperback) 1st Edition. Springer-Verlag New York, Inc. ISBN 0-387-95475-9 (download link)  P. M. McCullagh and John A. Nelder. Generalized Linear Models. 2nd Edition. Chapman and Hall, London. ISBN 978-0412317606. (download link)  T. J. Hastie and R. J. Tibshirani. Generalize Additive Models. Chapman and Hall, London. ISBN: 0-412-34390-8  David Rupert, M. P. Wand, and R. J. Carroll. Semiparametric Regression. Cambridge University Press. ISBN 978-0521785167  W. N. Venables and B. D. Ripley. 2002 Modern Applied Statistics with S. 4th Edition. Springer. ISBN 0-387-95457-0 Other Useful Reference:  An Introduction to R. Online manual at R website at http://cran.r-project.org/manuals.html  Andreas Krause, Lelvin Olson. 2005. The Basics of S-PLUS. 4th Edition. Springer-Berlag, New York. ISBN 0-387-26109-5  Jose Pinheiro and Douglas Bate. 2000. Mixed-effects models in S and S-PLUS. Springer-Verlag, Berlin. ISBN 0-387-98957-9