Statistics - Survival Analysis
4 & 5 October 2023 and 1 & 2 October 2024
Royal Statistical Society
Summary
- Certificate of Attendance - Free
- Tutor is available to students
Add to basket or enquire
Location & dates
Errol Street
City of London
London
EC1Y8LX
United Kingdom
Overview
This course is being held on 4 & 5 October 2023 and 1 & 2 October 2024
Standard methods of survival analysis based on the Kaplan-Meier estimate of a survivor function, the log rank test and Cox regression modelling are widely used in many different areas of application. But often, the assumptions that underlie these techniques may not be valid, or the data structure may be more complex. Extensions of these basic methods allow particular features of data that occur in practice to be handled appropriately. This course will begin with an overview of standard methods and then move on to some of the more advanced techniques. Their practical application will be illustrated using SAS and R.
Certificates
Certificate of Attendance
Hard copy certificate - Included
Description
Standard methods of survival analysis based on the Kaplan-Meier estimate of a survivor function, the log rank test and Cox regression modelling are widely used in many different areas of application. But often, the assumptions that underlie these techniques may not be valid, or the data structure may be more complex. Extensions of these basic methods allow particular features of data that occur in practice to be handled appropriately. This course will begin with an overview of standard methods and then move on to some of the more advanced techniques. Their practical application will be illustrated using SAS and R.
Learning Outcomes
An appreciation of how the methods of survival analysis can be used in a variety of situations.
Topics Covered
Overview of standard methods for summarising survival data and the Cox regression model. Model selection strategy. Incorporating time dependent variables and the counting process formulation of survival data. Parametric models for survival data, including flexible models based on splines. Detecting and handling non proportional hazards. Incorporating random effects into a survival analysis; frailty models. Analysis of data where there is more than one type of event; models for competing risks. Dependent censoring.
Who is this course for?
Statisticians and epidemiologists in public sector research organisations, pharmaceutical companies and related organisations. University research students and fellows.
Requirements
Some familiarity with basic methods for summarising survival data, including estimates of the survivor function and the log rank test. Some experience in using the Cox regression model would be advantageous.
Questions and answers
Reviews
Currently there are no reviews for this course. Be the first to leave a review.
Add to basket or enquire
Course provided by
Legal information
This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
