Who should attend?

Epidemiologists, statisticians, physicians and oncologists, public health specialists and others with an interest in methods for studying cancer patient survival; particularly those working in a cancer registry or analysing cancer registry data.

The primary focus of the course is on statistical methods, but a degree in statistics or mathematical statistics is not required. We expect participants to have varied backgrounds and our experience is that participants benefit most if they have some prior knowledge of the following areas:

  1. statistical methods, especially methods for survival analysis;
  2. application of statistical models in medical research, particularly epidemiology; and
  3. cancer epidemiology and the diagnosis, treatment, and registration of cancer.

Very few participants will be extremely strong in all three areas - the level of knowledge in statistical methods, for example, is typically inversely proportional to the level of knowledge about cancer. We focus heavily on application of the methods so knowledge of cancer epidemiology and cancer is beneficial, as is experience with statistical modelling (even if it is logistic regression rather than survival analysis). Non-statisticians should not be discouraged from attending simply because the course covers some relatively advanced statistical methods. We have received very positive feedback from clinicians who attended previous courses, and the faculty values the input of participants with knowledge that complements their own. The wide range of backgrounds and knowledge among participants gives rise to many interesting and informative discussions, which we see as one of the strengths of this course.

We also welcome participants with interests in areas other than population-based cancer survival but potential participants should be aware that the focus of the course is the analysis of data collected by population-based cancer registries. We are happy, however, to work during the lab sessions with people interested in applying the methods in other areas.

We expect participants to possess basic knowledge of the fundamentals of epidemiology and biostatistics and be comfortable fitting statistical models in epidemiology (e.g., logistic regression, Poisson regression, or Cox regression). Based on past experience we know that participants will have a wide range of backgrounds. Some of the content will be directed at those with formal training in statistics, but the main emphasis of the course will be on concepts and application with a minimum of complex mathematical detail. Participants will gain most if they have some previous knowledge of basic concepts in survival analysis such as survival functions, Kaplan-Meier curves, and Cox regression.