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 workshop gives an introduction to time-to-event (survival) data for non-statisticians, and covers the following topics:Use of Kaplan-MeierLife tablesCox regression analysesHazard ratiosHow to set the data up for analysisIncluding interaction terms in the modelsAssessing modelInterpretation of SPSS outputSPSS 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.