Cox Regression with Steve Simon
When you have data measuring the time to an event, you can examine the relationship between various predictor variables and the time to the event using a Cox proportional hazards model.
In this webinar, you’ll see what a hazard function is and describe the interpretations of increasing, decreasing, and constant hazard. Then you’ll examine the log rank test, a simple test closely tied to the Kaplan-Meier curve, and the Cox proportional hazards model.
Date and Time
Wednesday, September 14, 2016 at 2:00 pm EDT (GMT -4)
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About the Instructor
Steve Simon works as an independent statistical consultant and as a part-time faculty member in the Department of Biomedical and Health Informatics at the University of Missouri-Kansas City. He has previously worked at Children’s Mercy Hospital, the National Institute for Occupational Safety and Health, and Bowling Green State University.
Steve has over 90 peer-reviewed publications, four of which have won major awards. He has written one book, Statistical Evidence in Medical Trials, and is the author of a major website about Statistics, Research Design, and Evidence Based Medicine, www.pmean.com. One of his current areas of interest is using Bayesian models to forecast patient accrual in clinical trials. Steve received a Ph.D. in Statistics from the University of Iowa in 1982.
Not a Member Yet?
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Just head over to our enrollment page to sign up for Statistically Speaking (formerly Data Analysis Brown Bag). You’ll get exclusive access to this month’s webinar on Cox Regression, plus open Q&A sessions and much more.