The course is connected to the following study programs

Recommended prerequisites

  • EX-602 Philosophy of Science

  • ME-626 General Quantitative Research Methods, ME-428 or corresponding courses

Course contents

  • Assumptions for performing logistic regression

  • Analysis with categorical independent variables

  • Analysis with continuous independent variables

  • Critical evaluation of models

  • Prediction of outcome with respect to sensitivity and specificity as well as predictive values

Learning outcomes

On successful completion of the course, the student has:

 

Knowledge about

  • the assumptions with respect to logistic regression

  • logistic regression models

Skills

  • can perform and critically evaluate logistic regression analysis with categorical and continuous independent variables

  • can predict outcomes with respect to sensitivity and specificity as well as predictive values

General competence

  • can independently plan, analyze, report and interpret own logistic regression analysis

  • can interpret and critically evaluate logistic regression analysis from published research

Examination requirements

Participation in compulsory lectures as stated in the course pamphlet.

Teaching methods

Lectures combined with practical statistical exercises in a computer lab. Examples of analysis of data will to a great degree be connected to the faculty’s on-going or planned research projects.

Assessment methods and criteria

Individual 5-days home examination. The examination will be assessed as pass/fail.

Last updated from FS (Common Student System) July 1, 2024 1:54:45 AM