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Module 5: Regression Methods -- Concepts and Applications

Instructors: Rebecca Hubbard, PhD (she/her/hers) and Xu Shi, PhD (she/her/hers)

Welcome

Overview

Overview

This module consists of a series of pre-recorded lectures that will introduce you to the basic concepts of regression for the analysis of associations between continuous or binary outcome variables and one or more predictor variables. Lectures are available for you to watch on your own and will be followed by interactive sessions in which we will go over any questions that you have and get hands-on experience applying these concepts to the analysis of data using R. Students are asked to watch the recorded lectures in advance of live sessions and work through labs using R (link to download R and RStudio).

Link to zoom sessions was emailed to participants (subtitle: "Welcome to SISG Module 5") and posted on Slack.

Schedule

Wed 7/15

  • On your own: Simple Linear Regression -- Part 1 (video, slides pages 1-32)
  • On your own: Simple Linear Regression -- Part 2 (video, slides pages 32-58)
  • 1:30 -- 2:30PT: Questions and lab exercises 1--3 (labs, solutions, R codes)

Thurs 7/16

  • On your own: Model checking -- Part 1 (video, slides pages 1-15)

  • On your own: Model checking -- Part 2 (video, slides pages 15-35)

  • 10:30 -- 11:30PT: Questions and lab exercises 4--6 (labs, solutions, R codes)

  • On your own: Multiple linear regression -- Part 1 (video, slides pages 1-24)

  • On your own: Multiple linear regression -- Part 2 (video, slides pages 24-49)

  • 1:30 -- 2:30PT: Questions and lab exercises 7--8 (labs, solutions, R codes)

  • On your own: One-way ANOVA (video, slides pages 1-44)

Fri 7/17

  • On your own: Multiple comparisons and two-way ANOVA -- Part 1 (video, slides pages 45-68)

  • On your own: Multiple comparisons and two-way ANOVA -- Part 2 (video, slides pages 68-93)

  • 10:30 -- 12:00PT: Questions and lab exercises 9--12 (labs, solutions, R codes)

  • On your own: Logistic regression and generalized linear models -- Part 1 (video, slides pages 1-30)

  • On your own: Logistic regression and generalized linear models -- Part 2 (video, slides pages 31-56)

  • 1:30 -- 2:30PT: Questions and lab exercises 13--17 (labs, solutions, R codes)