course-details-portlet

KLMED8018 - Longitudinal data analysis

About

Examination arrangement

Examination arrangement: Home examination
Grade: Passed / Not Passed

Evaluation Weighting Duration Grade deviation Examination aids
Home examination 100/100 7 days

Course content

The course gives an introduction to the analysis of longitudinal data for studies with a continuous outcome variable. Longitudinal study designs, in which individual measurements are taken repeatedly over time, will be described, as well as descriptive statistics for longitudinal data. The course includes linear mixed models (multi-level models), and in addition marginal models where the correlation structure for the repeated measurements is specified directly and not by the means of a multilevel model. Models with time treated as a categorical variable as well as models with a continuous time variable will be discussed. Description of various correlation structures for modeling the time dependency, and 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 importance of dependency in longitudinal data for the statistical analysis and modeling, and the consequences of not accounting for this dependency
  • have knowledge of multilevel models (linear mixed models) and marginal models for longitudinal data, and the difference between them
  • 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 longitudinal data by simple descriptive analyses and graphical displays
  • identify the appropriate statistical method for analyzing a set of longitudinal data, including the correlation structure for the time dependency
  • independently perform a statistical analysis for longitudinal data by the means of statistical software
  • 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 longitudinal data in medical research projects

Learning methods and activities

Lectures and exercises

Course materials

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

More on the course

No

Facts

Version: 1
Credits:  3.0 SP
Study level: Doctoral degree level

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2024

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Medicine
  • Statistics
Contact information
Course coordinator:

Department with academic responsibility
Department of Public Health and Nursing

Timetable

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Examination

Examination arrangement: Home examination

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Home examination 100/100

Release
2024-09-27

Submission
2024-10-04


09:00


12:00

INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

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