Statistical methods for population-based cancer survival analysis
There will not be a course in Italy in 2017. We will instead teach a similar course in conjunction with the NAACCR 2017 Annual Conference in Albuquerque, New Mexico, USA. The course will run for 4 days, June 16-19, and registration is now open. We plan to be back at the summer school in June 2018.
As part of the Summer School on Modern Methods in Biostatistics and Epidemiology, a highly experienced faculty will present an intensive 1-week course on the principles, methods and application of statistical methods in population-based cancer survival analysis.
The course will cover central concepts, such as how to estimate and model relative/net survival, as well as recent methodological developments including cure models, flexible parametric models, proportion of expected life lost, and estimating crude probabilities of death. Comparison of alternative methodological approaches (e.g., to estimating relative survival and to modelling relative survival) will will be a focus of the course and participants will get the opportunity to apply and contrast a range of methods to real data. The course will consist primarily of lectures and hands-on computing sessions with a focus on individual instruction and discussion. Click here for further details of the course content.
Our goal is to provide each participant with individual instruction. A large amount of time will be devoted to exercise sessions where 5 faculty members will be available to work with participants individually or in small groups. We will provide an extensive set of exercises with fully-worked solutions but the exercise sessions will also provide an opportunity for participants to discuss their own research projects with the faculty (and with each other). Participants are welcome to bring a laptop with their own data; we are happy to discuss how such data can be analysed. Our goal is that, after completing the course, participants will return to their home institution with both the theoretical knowledge, practical skills, and computing code (e.g., Stata or SAS code) to perform survival analyses.
We have chosen the venue since we believe a residential course in a pleasant environment provides much more than a "nine to five" course. The faculty will stay at the course venue and look forward to discussions not just during the course but during breakfast, dinner, and after dinner.
Primary teachers: Paul Dickman and Paul Lambert
Teaching assistants: Sandra Eloranta plus two more to be confirmed.
[Click here for faculty biographies]
Date and Location
Who should attend
Epidemiologists, statisticians, physicians and oncologists, public health specialists and others with an interest in methods for studying cancer patient survival. [Further information]
Course fee and registration
See the home page of the Summer School on Modern Methods in Biostatistics and Epidemiology for information on the course fee, accommodation, and registration.
A significant amount of time will be allocated to hands-on computing sessions where participants will have the opportunity to apply the methods described in the course to real data. Stata version 14 will be the primary course software and a time-limited licence will be provided. Paul Lambert and Paul Dickman have each developed Stata commands for estimating and modelling relative survival. We will provide extensive exercises with worked solutions as well as Stata do files that participants can use as templates for analying their own data. Paul Lambert and Paul Dickman also have experience applying these methods in other software, such as SAS, R, and WinBUGS, and are willing to assist participants who wish to work with these packages but not all of the methods described in the course can be applied in other packages and we do not have the same level of expertise in other packages as we do in Stata. The computing sessions are also intended as a forum for participants to talk to the faculty about aspects of particular interest to them; five faculty members will be in attendance during each session which will make individual instruction possible. The course is designed to be accessible to participants without previous experience of using Stata.
The school will provide computers, but many participants prefer to bring their own laptop to ensure a familiar keyboard layout and software.
Course certificate and assessment
Each participant will receive a certificate of attendance. There is no formal examination. The course is not an official university course and successful completion of the course does not automatically entitle academic credits although registered students may be able to apply to their university for formal credit.
The course language will be English. All instruction and course materials will be in English.
The course is organised by the Summer School on Modern Methods in Biostatistics and Epidemiology.