# EPSY8282, Spring 2011

## Class Notes

- Class 1: Language of Longitudinal Data
- Class 2: R Introduction | R
- Class 3: Profile Plots | R
- Class 4: Exploring Correlations | R
- Class 5: Simple Analyses | R
- Class 6: Why Not Use Simple
Analyses?
- Class 7: Multivariate Normal Model | R
- Class 8: The Covariance Matrix | R
- Class 9: Adding Covariates | R
- Class 10: Reviewing the Multivariate Normal Model | R
- Class 11: Likelihood | R
- Class 12: Information Criteria and Inference | R
- Case: Pediatric Pain
- Class 14: an additive model | R
- Class 15: an interaction model; setup | R
- Class 16: an interaction model; fitting in R and testing hypotheses | R
- Case: Cognitive Data
- Class 17: Part One | R
- Class 18: Part Two | R
- Case: BSI Data
- Class 19: Bent Lines | R
- Case: Wallaby tails
- Class 20: Curves and Splines | R
- Case Studies for testing Covariance Matrices
- Class 24: Student data from HW3
- Class 25: Pediatric Pain | R
- Class 26: Small mice data | R

## Assignments

- Homework 1 (due Jan 28): Exploring a longitudinal data set
- Homework 2 (due Feb 18): Simple analyses
- Homework 3 (due Mar 11): Fitting and comparing multivariate normal models
- Homework 4 (due Apr 1): Models with changes from a baseline due to a treatment
- Homework 5 (due Apr 29): Fitting various covariance structures
- Final Project (due May 14)