course-details-portlet

KLMED8022

Multilevel and longitudinal data analysis

New from the academic year 2025/2026

Credits 5
Level Doctoral degree level
Course start Autumn 2025
Duration 1 semester
Language of instruction English
Location Trondheim
Examination arrangement Home examination

About

About the course

Course content

The course introduces the analysis of multilevel and longitudinal data (clustered data) for continuous and binary outcome measures. Advantages and challenges with the dependencies in clustered data will be discussed. Longitudinal study designs, in which individual measurements are taken repeatedly over time, will be given special focus.

The course covers descriptive statistics for multilevel and longitudinal data, covariance and correlation, variance components, and statistical analyses by linear mixed models. For longitudinal data, analysis of summary measures (e.g. AUC, linear slope, min/max values) and models with a categorical as well as a continuous time variable will be presented.

In addition, marginal models where the correlation structure for the repeated measurements is specified directly and not by the means of a multilevel model, including generalized estimating equations (GEE), will be discussed. How to choose the model that gives the best fit to the data, will be emphasized. Methods for longitudinal data from randomized studies with a pre-post design will be discussed particularly. The course includes exercises using the Stata software.

Learning outcome

Knowledge

After successful completion of this course the student should

  • be aware of the nature of dependency in clustered measurements, and how this dependency influences the approach to analysis and modeling, as well as the consequences of ignoring this dependency
  • have knowledge of marginal and multilevel models (linear and logistic mixed models) for clustered data, and the difference between these models
  • have knowledge of how and when these methods can be applied in medical research projects

Skills

After successful completion of this course the student should be able to

  • summarize multilevel and longitudinal data by simple descriptive analyses and graphical displays
  • identify clusters and potential dependency by inspecting the design and/or the resulting data set for a study
  • identify the appropriate statistical method for analyzing a set of clustered data
  • identify an appropriate correlation structure for the time dependency in longitudinal data
  • independently perform a statistical analysis for multilevel and longitudinal data by the means of statistical software (Stata)
  • evaluate the assumptions made on the applied model or method
  • interpret and critically evaluate the results from the statistical analysis
  • present the results in a format applicable for publication in a scientific medical journal

General competence

After successful completion of this course the student should

  • be able to evaluate application of statistical methods for analyses of multilevel and longitudinal data in medical research projects

Learning methods and activities

Lectures and exercises using Stata.

Further on evaluation

By a re-set examination the type of assessment could be changed to oral examination.

Course materials

Rabe-Hesketh & Skrondal (2022). Multilevel and Longitudinal Modeling Using Stata; Volume 1: Continuous Responses, and Volume II: Categorical Responses, Counts and Survival. 4th ed. Stata Press

Lecture notes and additional papers

Credit reductions

Course code Reduction From
KLMED8017 3 sp Autumn 2025
KLMED8018 3 sp Autumn 2025
KLMED8008 5 sp Autumn 2025
This course has academic overlap with the courses in the table above. If you take overlapping courses, you will receive a credit reduction in the course where you have the lowest grade. If the grades are the same, the reduction will be applied to the course completed most recently.

Subject areas

  • Medicine
  • Statistics

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of Public Health and Nursing

Examination

Examination

Examination arrangement: Home examination
Grade: Passed / Not Passed

Ordinary examination - Autumn 2025

Home examination
Weighting 100/100 Date Release 2025-10-13
Submission 2025-10-24
Time Release 09:00
Submission 12:00
Duration 7 days Exam system Inspera Assessment