Module 5.4: Hierarchical normal modeling of means and variances

Required:

• A First Course in Bayesian Statistical Methods by Peter D. Hoff.:
  • Section 8.4: Example: Math scores in U.S. public schools
  • Section 8.5: Hierarchical modeling of means and variances
  • Section 8.6: Discussion and further references

Optional:

• Bayesian Data Analysis (Third Edition) by Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin.:
  • Section 5.3: Fully Bayesian analysis of conjugate hierarchical models
  • Section 5.4: Estimating exchangeable parameters for a normal model
  • Section 5.5: Example: parallel experiments in eight schools
  • Section 5.7: Weakly informative priors for hierarchical variance parameters