Course - Analysis of Repeated Measurements - KLMED8008
KLMED8008 - Analysis of Repeated Measurements
About
This course is no longer taught and is only available for examination.
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.
Recommended previous knowledge
KLMED8004 and KLMED8005, or equivalent.
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 |
No
Version: 1
Credits:
5.0 SP
Study level: Doctoral degree level
Language of instruction: English, Norwegian
Location: Trondheim
- Medicine
- Statistics
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.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"