Workshop

Guilherme J. Rosa, Department of Animal Science and the Department of Biostatistics & Medical Informatics, University of Wisconsin - Madison

Guilherme J. M. Rosa, Department of Animal Science and the Department of Biostatistics & Medical Informatics, University of Wisconsin – Madison

2018 Workshop Topic:

Introduction to Graphical Modeling for Agricultural Data

The workshop will provide an introduction to graphical models, with a focus on directed acyclic graphs (DAG). Methodologies to be discussed include path analysis, structural equation models, and Bayesian networks. The material will cover some key concepts and practical tools. Examples will be used to illustrate applications on prediction and causal inference in agriculture.

  1. Correlation and causation, observational and experimental data
  2. Confounding and selection bias
  3. Directed Acyclic Graphs (DAG)
  4. Conditional independence and the concept of d-separation
  5. Structural equation models with fixed and random effects
  6. Bayesian networks; structure learning and parameter learning
  7. Prediction and causal inference
  8. Examples in agriculture