|
Date |
Lecture |
PART I - Generalized Linear Models |
1 |
Mon Jan 4 |
Overview / examples / issues |
2 |
Wed Jan 6 |
GLMs & likelihood theory |
3 |
Fri Jan 8 |
Multinomial models: POM |
4 |
Mon Jan 11 |
Multinomial models: CRM |
5 |
Wed Jan 13 |
Overdispersion (semi-parametric) |
6 |
Fri Jan 15 |
Quasilikelihood & estimating functions |
7 |
Mon Jan 18 |
HOLIDAY - No Class |
8 |
Wed Jan 20 |
Empirical variance estimates & QL inference |
9 |
Fri Jan 22 |
Overdispersion (parametric models) |
PART II - General Linear Model for Correlated Continuous Data |
10 |
Mon Jan 25 |
General linear model, balanced data |
11 |
Wed Jan 27 |
Weighted least squares & EEs |
12 |
Fri Jan 29 |
Models & estimation for variance components |
13 |
Mon Feb 1 |
Experimental design & classical ANOVA methods |
14 |
Wed Feb 3 |
General linear models for unbalanced data |
15 |
Fri Feb 5 |
Maximum likelihood, restricted maximum likelihood |
16 |
Mon Feb 8 |
Linear mixed models |
17 |
Wed Feb 10 |
Prediction of random effects |
18 |
Fri Feb 12 |
Longitudinal data analysis |
19 |
Mon Feb 15 |
HOLIDAY -- No Class |
PART III - Correlated Discrete Data
|
20 |
Wed Feb 17 |
Diagnostics for general linear models |
21 |
Fri Feb 19 |
Marginal, conditional & transition models |
22 |
Mon Feb 22 |
Generalized estimating equations (GEE) |
23 |
Wed Feb 24 |
Extensions of GEE & association models |
24 |
Fri Feb 26 |
Generalized linear mixed models (GLMMs) |
25 |
Mon Mar 1 |
Conditional likelihood for GLMMs |
26 |
Wed Mar 3 |
GLMMs vs marginal models |
27 |
Fri Mar 5 |
Transition models |
28 |
Mon Mar 8 |
Time-dependent covariates |
29 |
Wed Mar 10 |
Missing data (drop-out) |
30 |
Fri Mar 12 |
Summary |