Course content - Learning outcome - Admission - Prerequisites - Teaching - Examination - Evaluation

Course content

1. Analysis of contingency tables, 2x2 tables and rxc tables. Measures of effect. The chi-square test, Fisher’s exact test.
2. Stratified analyses, the Mantel Haenszel estimator.
Confounding and effect modification.
3. Simple logistic regression
4. Multiple logistic regression

Learning outcome

The course is intended to give an understanding of concepts and methods related to analysis of categorical data, with focus on analysis of contingency tables and logistic regression. The course is based on the SPSS software.

Admission

Id does not exist in shared text

Ph.D. candidates and students at the Medical Student Research Programme will get first priority to the course. Maximum number of particpants is 35.

Registration in the Studentweb - 1st December until 20th December.

Registration for applicants without access to the StudentWeb - 1st December until 20th December.

Applicants will be notified by email 1 - 2 weeks after the final date for registration.

Id does not exist in shared text

Prerequisites

Formal prerequisite knowledge

Id does not exist in shared text

It is required that the participants have been through the MF9130E Introductory course in statistics /MF9130 Innføring i statitstikk or equivalent.

Recommended previous knowledge

Some knowledge of linear regression models.

Teaching

The course is organized as full day teaching over 4 days and includes lectures and exercises in PC-labs.

The course will be taught 14.1.-17.1.2013

NB! You have to participate in at least 80 % of the teaching to be allowed to take the exam. Attendance at lectures will be registered.

Access to teaching

Id does not exist in shared text

Examination

A take-home exam will be given at the end of the course. Grading: pass/fail.

Examination support material

Id does not exist in shared text

Language of examination

Id does not exist in shared text

Grading scale

Id does not exist in shared text

Explanations and appeals

Id does not exist in shared text

Students can request an explanation of their grades, and can also appeal against their grades or make a complaint about formal examination errors. Read more about explanations and appeals

Resit an examination

Id does not exist in shared text

Withdrawal from an examination

Id does not exist in shared text

Special examination arrangements

Id does not exist in shared text

Evaluation

Feedback from our students is essential to us in our efforts to ensure and further improve the high quality of our programmes and courses. All courses are subject to continuous evaluation. At regular intervals we also ask students on a particular course to participate in a more comprehensive, periodic evaluation of this course.