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

• 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.

PhD students and students at the Student Research Program at UiT - The Arctic University of Norway go directly to Studentweb to register for class and exam. Deadline for registration is February 1st.

Other applicants: Application deadline is December 1st. Application code 9303 in Søknadsweb.

If granted admission to the course you have to register for class and exam in Studentweb by February 1st.

PhD students or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted. PhD students must upload a document from their university stating that they are registered PhD students. This group of applicants does not have to prove English proficiency and are exempt from semester fee.

Holders of a Master´s degree must upload a Master´s Diploma with Diploma Supplement / English translation of the diploma. Applicants from listed countries must document proficiency in English. To find out if this applies to you see the following list:

Proficiency in English must be documented - list of countries

For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see the following document: Proficiency in English - PhD level studies

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.

Mandatory work requirements: Attendance to lectures and seminars

Exam and evaluation The exam consists of a written assignment to be submitted 14 days after the assignment is distributed. Evaluated with pass / fail.

Continuation exam The course is held annually, no continuation exam.

The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.