Causal Inference, Certificate

  • N/A
    Application Deadline
  • 5 days
    Duration
  • Tuition
    710
    Tuition (Module)
    710
    Tuition (Module)
  • English (take IELTS)
    Language

About

The goal of many epidemiologic studies is to quantify the causal effect of an exposure on an outcome. In contrast, commonly used statistical methods provide measures of association that may lack a causal interpretation even when the investigator adjusts for all potential confounders in the analysis of a properly designed study.

To eliminate the discordance between the causal goals and the associational methods in epidemiology, it is necessary to a) formally define causal concepts such as causal effect and confounding, b) identify the conditions required to estimate causal effects, and c) use analytical methods that, under those conditions, provide estimates that can be endowed with a causal interpretation. These (causal) methods can be used under less restrictive conditions than traditional statistical methods.

For example, causal methods allow one to estimate the causal effect of a time-varying exposure in the presence of time-dependent confounders that lie on the causal pathway between exposure and outcome.

This course combines counterfactual theory and graph theory to present an integrated framework for causal inference from observational data, with a special emphasis on complex longitudinal data. The course presents the latest methodologic developments for the design and analysis of longitudinal studies. 15 hrs.

Objectives:
  • Recognize and formulate well defined questions concerning causal effects
  • Use causal diagrams to represent a priori subject-matter knowledge and assumptions
  • Identify the settings in which conventional methods for data analysis are inadequate

Detailed Programme Facts

  • Full-time duration 5 days
  • Languages
    • English
  • Delivery mode
    On Campus

Programme Structure

  • Course code: ESP48
  • Faculty: Miguel Hernán
  • Time: 08:45 11:45
  • Course days: Monday to Friday
  • Course material: Online, download instructions will be sent in August by e-mail. A laptop is recommended.
  • Prerequisites: Intermediate-level courses in epidemiology and biostatistics. Previous experience in epidemiologic research recommended.

Lecturers

Dr. Miguel Hernán

English Language Requirements

This programme requires students to demonstrate proficiency in English.

Take IELTS test

Academic Requirements

  • Intermediate-level courses in epidemiology and biostatistics. Previous experience in epidemiologic research recommended.

Tuition Fee Per Module

  • EUR 710 International
  • EUR 710 EU/EEA

Funding

Each year, the Erasmus Summer Programme provides international students and professionals with an invaluable opportunity to spend three weeks in Holland, bringing themselves right up to date in the health sciences. In just three weeks, the Erasmus Summer Programme provides 30 courses on state-of-the-art biomedical topics. Each course is designed to fully satisfy the needs of international students with a specific interest such as clinical medicine, general practice, public health, epidemiology, genetics or biostatistics.

A key part in the Erasmus Summer Programme is played by the Fellowships: three suites of courses that provide top-level instruction in clinical research training, public health research, and genetic epidemiology. Each Fellowship is a stimulating challenge for talented young scientists who seek leading careers in scientific research.

Between them, the Erasmus Summer Programme and the Fellowships make a vital contribution to life-long learning and the professional development of students and teachers. By attracting ever greater interest each year, they reveal the enormous international demand for a springboard to an MSc or PhD in quantitative medicine or public health research.

StudyPortals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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