MW 11:30-12:20, F 13:30-14:20
Week |
Topic |
Reading/notes |
Assignments |
1 (6 Sep) |
Introduction, overview, logistics; R basics, data visualization |
DB pp. 1-5 |
|
2 (9, 11, 13 Sep) |
Distributions and estimation; model fitting; design matrices and contrasts |
DB rest of ch.1, ch. 2 |
|
3 (16, 18, 20 Sep) |
General linear models (ANOVA, regression, ANCOVA, etc.) |
DB ch. 6 |
problem set 1 (Mon.) |
4 (23, 25, 27 Sep) |
Exponential family and GLMs; estimation | DB ch. |
|
5 (30 Sep, 2, 4 Oct) |
Inference | DB ch. 5 |
PS 2 |
6 (7, 9, 11 Oct) |
Logistic regression |
DB ch. 7 |
|
Thanksgiving (14 Oct) |
|||
7 (16, 18 Oct) |
Review and midterm exam |
PS 3 (Mon.) | |
8 (21, 23, 25 Oct) |
Count data (Poisson, negative binomial models), binomial models, overdispersion |
DB ch. 9 |
|
9 (28, 30 Oct) |
Nominal and ordinal data; conditional logistic regression |
DB ch. 8 |
PS 4 (Thurs.) |
10 (4, 6, 8 Nov) |
Survival analysis |
DB ch. 10 |
|
11 (11, 13, 15 Nov) |
Bayesian approaches |
DB ch. 13-14 |
PS 5 (Thurs.) |
12 (18, 20, 22 Nov) |
Multilevel models |
||
13 (25, 27, 29 Nov) |
Multilevel models, continued |
PS 6 (Thurs.) |
|
14 (2, 4 Dec) |
Wrap-up |