course-details-portlet

KLMED8008 - Analysis of Repeated Measurements

About

This course is no longer taught and is only available for examination. For a complete course description, see previous academic years.

Examination arrangement

Examination arrangement: Home examination
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Home examination 100/100 1 weeks A

Course content

Problems and advantages with dependent observations. Summary measures (Area under curve (AUC), coefficient of slope, min/max value).Covariance and correlation.Adjustment for baseline measurement.Variance components. Linear mixed effect models.Use of relevant software (Stata)

Learning outcome

After completing the course, the student should be able to: • Understand the nature of dependency in clustered and repeated measurements, and how this dependency alters the approach to statistical analysis and modeling; as well as the consequences of not taking this information into account • Identify clusters and potential dependency by inspecting the design and/or viewing the resulting data set • Understand the principles of experimental design in which experimental factors vary both between and within clusters • Perform simple, descriptive analyses such as obtaining sample covariance and correlation, and corresponding graphical plots such as scatter plots, to illuminate key features of data with clustered and/or repeated observations • Perform and interpret variance component estimation, and adjustment for baseline value in randomized trials using analysis-of-covariance • Perform and interpret linear mixed regression models with random intercept, with random intercept and random slopes for covariates; using appropriate software • Understand the special nature of observations made along the time axis, including the possibility of autoregressive residuals

Learning methods and activities

Lectures and guided excercises.Course information will be published at http://folk.ntnu.no/eiriksko/KLMED8008/KLMED8008v16.htmlbefore the course starts.

Required previous knowledge

Master or equivalent degree in medicine, health related subjects, or social sciences. Medical students at The Student Research Programme. Candidates with a lower degree may be assessed individually.

Course materials

Textbook: Rabe-Hesketh & Skrondal (2021). Multilevel and Longitudinal Modeling Using Stata; Volume 1: Continuous Responses. Stata Press (4th edition)

Credit reductions

Course code Reduction From To
KLMED8006 2.0 AUTUMN 2010
ST2303 2.0 AUTUMN 2010
KLMED8017 3.0 AUTUMN 2022
More on the course

No

Facts

Version: 1
Credits:  5.0 SP
Study level: Doctoral degree level

Coursework

Language of instruction: English, Norwegian

Location: Trondheim

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

Department with academic responsibility
Department of Public Health and Nursing

Examination

Examination arrangement: Home examination

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

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU