Syllabus del corso

Esporta

Introduction to the construction and interpretation of Directed Acyclic Graphs (DAGs) Causal Diagrams as tools for:

  1. represent assumptions about the relationships between variables in observational and randomized studies
  2. obtain from this representation a guide in pragmatic statistical analysis
  3. thanks to this representation, avoid common errors and biases in statistical analysis
  • Causality and Correlation between variables.
  • Graphical representation of causality between variables.
  • Simpson's paradox
  • Causal path between variables and characteristics: open, closed, backdoor, D-separation.
  • Characteristics of variables within a causal path: confounder, mediator, common cause, other.
  • Impact of study design on the possible distortion of causal relationships: the observational case-control study and eligibility criteria in randomized studies.

The concepts introduced from a theoretical point of view will always be accompanied by an example on simulated data analyzed with the STATA software.

The student will be asked to reproduce/integrate some calculations to be discussed together using a software chosen from: R, SPSS, STATA, SAS.

  1. Basic elements of probability calculation
  2. Construction of frequency tables and regression models with a statistical software chosen from: R, Stata, SAS, SPSS

Standard class

Slides

3 April 11-13 - Kythos Building in Monza
7 April 11-13 - Kythos Building in Monza
10 April 11-13 - Kythos Building in Monza
14 April 11-13 - Kythos Building in Monza

Quiz

Esporta

Introduction to the construction and interpretation of Directed Acyclic Graphs (DAGs) Causal Diagrams as tools for:

  1. represent assumptions about the relationships between variables in observational and randomized studies
  2. obtain from this representation a guide in pragmatic statistical analysis
  3. thanks to this representation, avoid common errors and biases in statistical analysis
  • Causality and Correlation between variables.
  • Graphical representation of causality between variables.
  • Simpson's paradox
  • Causal path between variables and characteristics: open, closed, backdoor, D-separation.
  • Characteristics of variables within a causal path: confounder, mediator, common cause, other.
  • Impact of study design on the possible distortion of causal relationships: the observational case-control study and eligibility criteria in randomized studies.

The concepts introduced from a theoretical point of view will always be accompanied by an example on simulated data analyzed with the STATA software.

The student will be asked to reproduce/integrate some calculations to be discussed together using a software chosen from: R, SPSS, STATA, SAS.

  1. Basic elements of probability calculation
  2. Construction of frequency tables and regression models with a statistical software chosen from: R, Stata, SAS, SPSS

Standard class

Slides

3 April 11-13 - Kythos Building in Monza
7 April 11-13 - Kythos Building in Monza
10 April 11-13 - Kythos Building in Monza
14 April 11-13 - Kythos Building in Monza

Quiz

Entra

Scheda del corso

Staff

    Docente

  • Rino Bellocco
    Rino Bellocco

Metodi di iscrizione

Iscrizione manuale
Iscrizione spontanea (Studente)