Textbook There will be no assigned textbook for this class in addition to the lecture slides and notes. However, the following is a list of useful references starting from the most applied book: Survival Analysis: Techniques for censored and truncated data (Statistics for biology and health) by John P. Klein and Melvin L Moeschberger (2005) The statistical analysis of failure time data by John D Kalbfleisch and Ross L. Prentice (2002) Counting Processes and survival analysis by Thomas Fleming and David P. Harrington (2005) Statistical models on counting processes by Per Kragh Andersen, Ornulf Borgan, Richard, D Gill and Niels Keiding (1997) We will also supplement the lecture notes with selected landmark research papers such as Cox’s original JRSSB paper on proportional hazards model. Software The course will teach how to perform survival analysis using R Assessment The assessment consists of weekly homework (40%), requiring either mathematical derivation using technique taught in the class or conduction of some real data analysis with R, and a take home course project, which will be given in the last week of the quarter (60%). Course website You may find the lecture notes, slides and homework at the website.
Textbook There will be no assigned textbook for this class in addition to the lecture slides and notes. However, the following is a list of useful references starting from the most applied book: Survival Analysis: Techniques for censored and truncated data (Statistics for biology and health) by John P. Klein and Melvin L Moeschberger (2005) The statistical analysis of failure time data by John D Kalbfleisch and Ross L. Prentice (2002) Counting Processes and survival analysis by Thomas Fleming and David P. Harrington (2005) Statistical models on counting processes by Per Kragh Andersen, Ornulf Borgan, Richard, D Gill and Niels Keiding (1997) We will also supplement the lecture notes with selected landmark research papers such as Cox’s original JRSSB paper on proportional hazards model. Software The course will teach how to perform survival analysis using R Assessment The assessment consists of weekly homework (40%), requiring either mathematical derivation using technique taught in the class or conduction of some real data analysis with R, and a take home course project, which will be given in the last week of the quarter (60%). Course website You may find the lecture notes, slides and homework at the website.
Stat331.docx