Introduction to Survival/Time-to-Event Data Analysis

Book Now (Hybrid)

NOTE: This course will be delivered in hybrid mode, i.e. the in-person lecture will be transmitted live on zoom. The face-to-face part of the hybrid courses will go ahead conditional on at least 5 participants registering for this mode of delivery. Few classes may be delivered exclusively online, so please check under the Future dates tab for clarification. The online part of the class will be supported by its own dedicated teaching staff (along with the lead lecturer), therefore participants can expect the same level of group and individual support as the face-to-face class. You will be able to choose your preferred mode of attendance (face-to-face or online) during registration.

Details

Survival/time-to-event analysis is appropriate when the outcome of interest is an event and that event has not occurred for everyone in the dataset. The outcome can be something negative (for example death, recurrence of tumour) or something positive (for example, recovery, task completion).

The simplest analysis is the log-rank test that assesses differences according to a single factor. Cox proportional hazards regression is appropriate to investigate the rate at which the event occurs according to several potential predictors.

This course gives an introduction to time-to-event (survival) data for non-statisticians, and covers the following topics:

• Use of Kaplan-Meier
• Life tables
• Cox regression analyses
• Hazard ratios
• How to set the data up for analysis
• Including interaction terms in the models
• Assessing model interpretation of SPSS output

SPSS outputs are given and we consider how to interpret these to determine the best model and to assess goodness-of-fit. The course will be of use to users of alternative statistical packages too as the concepts discussed throughout the course are generally applicable. The dataset may be taken away and analysed within other packages.

Note that this course does not involve hands on use of a stats package, we will consider only pre-prepared printouts.

Fees

Course fees

External Delegates (Non-UCL)	£150.00
UCL Staff and Students	£75.00 *
UCL Alumni	£75.00
Staff and Doctoral Students from ICH/GOSH	FREE †

* Valid UCL email address and/or UCL alumni number required upon registration. Please note, this category does not include hospital staff unless you hold an official contract with the university.

† Limited free spaces available. If there are no free places remaining, Staff and Doctoral Students from ICH/GOSH can still register at the UCL rate.

Cancellations

Finally, please note that no refunds will be given for non-attendance or cancellations made within 5 working days of the start of the course. For delegates attending courses on funded places, a £50 fee will be charged for late cancellation, non-attendance or partial-attendance.

Future Dates

Dates	Time	Apply
25th February 2025	9.30am - 5.00pm	Book Now

^We recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly at 9.30am.

Feedback

"Really enjoyed the course. It was very useful. The presentation was excellent. Very clear. Good pace. Allowed a good amount of time for questions and clarifying issues. Also enjoyed the practicals. Felt the course length was appropriate. Probably my favourite course out of all the ones I have done (and I have done a lot!)"

"Presentation was very well done. Student participation was spot on. Overall thank you for a very good course. I would recommend it to anyone interested in the subject"

"Overall a very good course. The quality of the teaching staff was high and they came across very friendly and open to questions. It was a good refresher course to me."

"Thank you. This was the greatest and clearest statistics course/lecture I have ever attended."

"I thought the content, presentation and detail of the course was of a high quality. The facilitator was very knowledge in the area and was able to target the course at a level that was suitable for an Introductory course. I would highly recommend this course to others."

"I found this course really useful. I really enjoyed the fact that it focused a lot on interpreting the results from other studies, rather than just how to do the analysis."

"Great course, well presented, the mini questions sections really helped solidify the content."