Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI

Digital N-of-1 trials and their application (Sommersemester 2024)

Lecturer: Dr. rer. nat. Stefan Konigorski (Digital Health - Machine Learning)
Course Website: https://moodle2.uni-potsdam.de/course/view.php?id=41443

General Information

  • Weekly Hours: 2
  • Credits: 3
  • Graded: yes
  • Enrolment Deadline: 01.04.2024 - 30.04.2024
  • Teaching Form: Seminar
  • Enrolment Type: Compulsory Elective Module
  • Course Language: English
  • Maximum number of participants: 20

Programs, Module Groups & Modules

IT-Systems Engineering MA
Data Engineering MA
Digital Health MA
Software Systems Engineering MA
  • MALA: Machine Learning and Analytics
    • HPI-MALA-C Concepts and Methods
  • MALA: Machine Learning and Analytics
    • HPI-MALA-T Technologies and Tools
  • MALA: Machine Learning and Analytics
    • HPI-MALA-S Specialization



Traditionally, treatment guidelines and health intervention recommendations are developed based on results of large cohort studies or randomized controlled trials (RCTs). However, the analysis of such studies only yields estimates of average effects. Hence, these results do not allow meaningful predictions whether an intervention will help a given single individual. In the advent of digital solutions, personalized approaches have been on the rise. N-of-1 trials and other modern study designs allow to derive individual treatment effects, but also to use the data to obtain and improve the precision of population-level effect estimates of health interventions. 


This seminar covers N-of-1 trials and other modern study designs such as micro-randomized trials. First, we will get an overview of different study types and their characteristics, then we will give an introduction of the practical aspects for performing N-of-1 trials, and then the main focus of the class will be on methodological approaches for planning and analyzing N-of-1 trials. 


  • Overview of classic and modern study designs
  • Introduction to N-of-1 trials
  • Ethics, data privacy and other requirements of digital studies
  • Standard methods for individual analysis of N-of-1 trials
  • Standard methods for aggregated analysis of N-of-1 trials
  • Bayesian regression models for N-of-1 trials
  • Meta analysis & network meta analyses
  • Sample size calculation for N-of-1 trials
  • Adaptive designs
  • Causal inference in N-of-1 trials


  • This seminar will be a mix of journal club and research seminar with applied data analysis
  • Introductory lectures with discussion of main concepts of N-of-1 trials and study designs
  • Introduction on technical aspects of performing digital N-of-1 trials
  • As part of the class, every student will run an N-of-1 trial and investigate the impact of self-determined interventions on sleep quality. The trial will be designed, implemented, and then run using the StudyU platform (studyu.health). All data will be collected anonymously and used throughout the course to illustrate the statistical methods.
  • Students will learn about all parts of the research process on N-of-1 trials including ethical issues, writing an ethics application, consent, data safety, and then data analysis and interpretation.
  • After the initial classes, readings of papers as homework and discussion in class. One group of students will lead the discussions
  • Joint statistical analysis of N-of-1 trial data gathered in class by applying the discussed statistical models.
  • Final project


1) Courses in statistics/machine learning/data science and in programming using R (e.g. "Biostatistics & Epidemiological Data Analysis using R" class)

2) Consent (will be provided in class) to record and publish data of self-designed and self-performed N-of-1 trials in class


This seminar will be a mix of journal club and research seminar with applied data analysis.


Final grade:

  • 20% participation in class
  • 30% moderation of session
  • 50% final project


Time: Wednesday, 17.15 - 18.45

First class: April 10, 2024

Location: G3.E15/16