American Statistical Association
What do Google page rank, Amazon.com's recommendations, and quitting smoking have in common? All three involve dynamic processes that can be understood by random walks on a network (or a "graph"). But is network analysis real progress or just a fad? Encouraged by network analysis on molecular oncogenic activation and cancer metastases, I am using it to understand smoking cessation dynamics in newly-diagnosed cancer patients who smoke. We tracked the daily cigarette consumption of 75 cancer patients from soon after diagnosis to hospitalization for surgery. In my talk, I will try to address these research questions: Are patients more likely to quit before surgery and stay quit if they quit cold turkey or if they cut down gradually? What is the probability that some cancer patients who smoke will never quit? Potential applications in other areas of cancer research will be discussed.
|Date:||Wednesday, September 19, 2012|
|Time:||4:00 P.M. - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.