Welcome

Here you find the schedule for our PhD course ‘Targeted Register Analysis’. Lecture notes and exercises are still under revision. Links to lecture notes and exercises will be available here on the first course day.

Venue

CSS = Center for Sundhed of Samfund Øster Farimagsgade 5, 1014 Copenhagen.

Weekday	Date	Room
Monday	11 December 2023	CSS 18.01.11
Tuesday	12 December 2023	CSS 5.0.22
Wednesday	13 December 2023	CSS 35.0.12
Thursday	14 December 2023	CSS 18.01.11

See map of CSS:

https://publichealth.ku.dk/contact/

Schedule

Monday 2023-12-11

8:15 – 8:20	Introduction to the course	Thomas Alexander Gerds
8:20 – 8:45	Lectures on Register Epidemiology: study design	Christian Torp-Pedersen
8:45 – 8:55	Coffee break
8:55 – 9:25	Exercise 1.1	Thomas Alexander Gerds
9:30 – 9:55	Lectures on risks, rates, counterfactuals	Christian Torp-Pedersen
10:00 – 10:30	Exercise 1.2	Thomas Alexander Gerds
10:30 – 10:40	Coffee break
10:40 – 11:05	Lectures on exposure versus outcome adjustment	Christian Torp-Pedersen
11:10 – 11:40	Exercise 1.3	Thomas Alexander Gerds
11:40 – 12:45	Lunch
12:45 – 13:10	Lectures on bias and confounding	Christian Torp-Pedersen
13:15 – 13:45	Exercise 1.4	Thomas Alexander Gerds
13:45 – 13:55	Coffee break
13:55 – 14:20	Lectures on The Analysis Plan	Christian Torp-Pedersen
14:25 – 14:55	Discussion and finishing Exercises	Thomas Alexander Gerds

Tuesday 2023-12-12

8:15 – 8:20	Introduction	Thomas Alexander Gerds
8:20 – 8:45	Lectures on The Roadmap of Targeted Learning	Andrew Mertens
8:45 – 8:55	Coffee break
8:55 – 9:25	Exercise 2.1	Thomas Alexander Gerds
9:30 – 9:55	Lectures on The Causal Roadmap	Andrew Mertens
10:00 – 10:30	Exercise 2.2	Thomas Alexander Gerds
10:30 – 10:40	Coffee break
10:40 – 11:05	Lectures on SuperLearning	Andrew Mertens
11:10 – 11:40	Exercise 2.3	Thomas Alexander Gerds
11:40 – 12:45	Lunch
12:45 – 13:10	Lectures on TMLE	Andrew Mertens
13:15 – 13:45	Exercise 2.4	Thomas Alexander Gerds
13:45 – 13:55	Coffee break
13:55 – 14:20	Lectures on a case study	Andrew Mertens
14:25 – 14:55	Discussion and finishing Exercises	Thomas Alexander Gerds

Wednesday 2023-12-13

8:15 – 8:20	Introduction	Thomas Alexander Gerds
8:20 – 8:45	Lectures on Machine Learning in Register Data (part I)	Marvin N. Wright
8:45 – 8:55	Coffee break
8:55 – 9:25	Exercise 3.1	Thomas Alexander Gerds
9:30 – 9:55	Lectures on Decision Trees & Random Forests (part II)	Marvin N. Wright
10:00 – 10:30	Exercise 3.2	Thomas Alexander Gerds
10:30 – 10:40	Coffee break
10:40 – 11:05	Lectures on Model Evaluation & Resampling (part III)	Marvin N. Wright
11:10 – 11:40	Exercise 3.3	Thomas Alexander Gerds
11:40 – 12:45	Lunch
12:45 – 13:10	Lectures on Penalized Regression & Ensemble Learning (part IV)	Marvin N. Wright
13:15 – 13:45	Exercise 3.4	Thomas Alexander Gerds
13:45 – 13:55	Coffee break
13:55 – 14:20	Lectures on Hyperparameter Tuning & Benchmarking (part V)	Marvin N. Wright
14:25 – 14:55	Discussion and finishing Exercises	Thomas Alexander Gerds

Thursday 2023-12-14

8:15 – 8:20	Introduction	Thomas Alexander Gerds
8:20 – 8:45	Lectures on time zero in hypothetical trials and registry data	Zeyi Wang
8:45 – 8:55	Coffee break
8:55 – 9:25	Exercise 4.1	Thomas Alexander Gerds
9:30 – 9:55	Lectures on longitudinal data structure and g-computation	Zeyi Wang
10:00 – 10:30	Exercise 4.2	Thomas Alexander Gerds
10:30 – 10:40	Coffee break
10:40 – 11:05	Lectures on censoring, missingness, confounding, competing risks	Zeyi Wang
11:10 – 11:40	Exercise 4.3	Thomas Alexander Gerds
11:40 – 12:45	Lunch
12:45 – 13:10	Lectures on time discretization and positivity	Zeyi Wang
13:15 – 13:45	Exercise 4.4	Thomas Alexander Gerds
13:45 – 13:55	Coffee break
13:55 – 14:20	Course evaluation	Thomas Alexander Gerds
14:25 – 14:55	Discussion and finishing Exercises	Thomas Alexander Gerds

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Navigation

Links to lecture notes and exercises will be available here