Validation of prediction models in epidemiology and medicine (2023)

Couse name: Validation of prediction models in epidemiology and medicine 2023

PhD Program: Epidemiology and Biostatistics

Description: While most medical studies aim to explain some phenomenon, a significant proportion does not have this as a primary goal. These studies instead aim to predict a certain event or measure as accurately as possible given a number of predictors. Although explaining and predicting are two separate goals, they are often interchanged in medical studies. More importantly, the statistical approaches used for these two types of data analyses are not the same. The course covers the following topics:

  1. The basic differences between explanatory and predictive studies.
  2. Model estimation: variable selection, variable predictive power and penalisation.
  3. Model Performance: N-fold cross validation, geographical and temporal validation, external validation.
  4. Model validity: Calibration and calibration slope, receiver operating characteristic (ROC) curve incl. area under the curve (AUC), Bland-Altman plots, prediction intervals and decision analysis.
  5. Examples from the scientific literature.

Upon completion of the course, the student will be able to distinguish between predictive and explanatory data analyses, as well as understand the basic statistical tools used in predictive studies.

Students will be evaluated based on an assignment with oral presentation in groups of 2-4 participants

Organizer: Lasse Hjort Jakobsen (lasse.j@rn.dk), Jan Brink Valentin (jvalentin@dcm.aau.dk)

Lecturers: Lasse Hjort Jakobsen, Jan Brink Valentin, Simon Grøntved

ECTS: 2.5

Dates: 24, 25, 26, 27 April 2023

Time: 08.30 to 16.00

Place: Selma Lagerløfs Vej 249, room 11.00.032

Zip code: 9260

City: Gistrup

Number of seats: 40

Deadline: 1 April 2023

Important information concerning PhD courses: None

Literature:

Moons K, Royston P, Vergouwe Y, Grobbee D, Altman D. Prognosis and prognostic research: what, why and how? BMJ2008;b375.

Ewout W. Steyerberg, Yvonne Vergouwe; Towards better clinical prediction models: seven steps for development and an ABCD for validation, European Heart Journal, Volume 35, Issue 29, 1 August 2014, Pages 1925–1931, https://doi.org/10.1093/eurheartj/ehu207

Requirements: Basic Statistics and basic programming abilities with Stata or R, all participants must bring a laptop with either Stata or R installed.

Important information concerning PhD courses:


We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.