| Course ID: | BIOS(STAT) 8140. 3 hours. |
| Course Title: | Multilevel and Hierarchical Models |
Course
Description: | Multilevel and hierarchical models for social and biological
sciences. Empirical Bayes, James-Stein, maximum likelihood, and
Bayesian estimation of model parameters. Interpreting and
diagnosing multilevel models, model building, and uncertainty
assessment. |
| Oasis Title: | MULTILEVEL MODELS |
| Prerequisite: | BIOS 7020 or STAT 6220 or STAT 6320 |
Semester Course
Offered: | Offered fall semester every year. |
| Grading System: | A-F (Traditional) |
|
| Course Objectives: | A student completing this course should be able to:
1. Describe multilevel models as a generalization of linear
regression models.
2. Describe multilevel models as a special case of a
hierarchical Bayes model.
3. Build, fit, and evaluate multilevel and hierarchical models
using classical and Bayesian methods.
4. Apply multilevel models to clustered sampling schemes,
growth curves, random coefficient settings, and grouped
experimental trials. |
| Topical Outline: | 1. Empirical Bayes and James-Stein Estimator
2. Multilevel Models
3. Model-checking using AIC/BIC/DIC
4. Maximum likelihood estimators, Fisher information, standard
errors and confidence intervals
5. Bayesian statistics, the slogan, computation with conjugate
priors
6. Random simulation and MCMC as a way to estimate a model,
confidence intervals
7. Fitting and interpreting models using WinBUGS and rube()
8. Using WinBUGS for simulation tests |