DSCI 562: Regression II

Approaches when faced with special conditions in regression, and consequences of ignoring these conditions.

Check out the About page for a description of the course.

Course Learning Objectives

By the end of the course, students are expected to:

Describe the risk and value of making parametric assumptions in regression.
Fit model functions that represent probabilistic quantities besides the mean.
Identify situations where standard linear regression is sub-optimal, and apply alternative regression methods that better address the situation.
Link the bias-variance tradeoff to the fundamental tradeoff of machine learning.

Deliverable	Weight	Deadline	Submit to...
lab assignment 1	15%	February 9, 2019 at 18:00	github.ubc.ca
lab assignment 2	15%	February 16, 2019 at 18:00	github.ubc.ca
quiz 1	20%	February 25, 2019 from 14:00-14:32	canvas (write in your lab room)
lab assignment 3	15%	March 3, 2019 at 15:00	github.ubc.ca
lab assignment 4	15%	March 9, 2019 at 18:00	github.ubc.ca
quiz 2	20%	March 12, 2019 from 11:00-11:32	canvas (write in DMP 301)

Note: Topics covered are conditional on time available.

Lecture	Date	Topic
1	2019-02-04	Model functions in regression
2	2019-02-06	Regression on restricted scales: GLM and transformations
3	2019-02-11	Regression beyond the mean
4	2019-02-13	Regression in the presence of outliers: robust regression
5	2019-02-25	Regression on censored response data: survival analysis
6	2019-02-27	Regression on ordinal response data: proportional odds model
7	2019-03-04	Regression when data are missing
8	2019-03-06	Regression in many groups: mixed effects models

If time remains, here are some topics we could cover:

List under construction

Julian J. Faraway. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition (Chapman & Hall/CRC Texts in Statistical Science), 2016.
For survival analysis: David G. Kleinbaum, Mitchel Klein (2012) Survival analysis: a self-learning text, 3rd edition
- Non-technical explanation of survival analysis, with a nice succinct summary along the side of each page.
- Recommends epidemiological background, but we will avoid those parts.