HEL-8002 Logistic Regression and Statistical Analysis of Survival Data - 3 stp

Two main topics are covered:

• Simple, multiple and stepwise logistic regression, matched case-control studies, and ordinal logistic regression
• Methods for analysis of survival data. Includes the Kaplan-Meier survival estimator, the log rank test, and Cox's Proportional Hazard regression model.

Other applicants apply for the right to study by June 1st for courses that are taught in the fall semester and December 1st for courses that are taught in the spring semester. Application is sent through SøknadsWeb. Please use the appliction code "9301 - Singular courses at the PhD level". If granted admission to the course students must register for class and exam in Studentweb by September 1st for autumn semester and February 1st for spring semester.

PhD students and students at the Student Research Programme, or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted. External PhD students and students at other Student Research Programmes, must upload a document from their university stating that they are registered students.

Admission recommendations:

Introductory course in medical statistics. It is recommended that students who are planning to take HEL-8024 complete it before taking this course.

Having attended the course and completed the exam the students will obtain the following learning outcomes:

Knowledge and understanding:

• Know how to specify a logistic regression model and a Cox proportional hazard regression model.
• Understand the difference between binary and ordinal logistic regression models.
• Understand when it is proper to use a logistic regression model.
• Understand when it is proper to use analysis of survival data.
• Interpret results from logistic regression models and analysis of survival data (Kaplan-Meier survival estimate, Cox regression models)

Skills:

• Be able to use a statistical package to analyse data using logistic regression models and models for the analysis of survival data (Kaplan-Meier survival function, log rank test, and Cox proportional hazard regression model).
• Identify different types of explanatory variables and correctly implement them in a logistic or Cox regression model.
• Be able to test interaction and assess confounding in logistic and Cox regression models.
• Evaluate the model assumptions

General Competence:

• Evaluate results from publications in medical journals where logistic models or Cox regression models are applied.
• Critically assess the validity of its use.