Old Chem 116
MWF 1:45 - 3:00pm (Fridays are lab sessions taught by TAs)
Note: office hours may vary due to travel and other commitments. Revisions to office hours will be noted via e-mail and on my office door.
Team member | Office hours | Location |
---|---|---|
Professor David Dunson | M/W 3-3:30pm | 218 Old Chemistry |
TA Patrick LeBlanc | Tuesday 1-3pm | 203B Old Chemistry |
TA Zhuoqun (Carol) Wang | Thursday 3:30-5pm | 203B Old Chemistry |
TA Shounak Chattapadhyay | Wednesday 12-1:30pm | 203B Old Chemistry |
You should have access to a laptop and bring it to every class, fully charged. Texts and readings will be assigned as needed. The instructor and TA’s will support computation in R/RStudio.
Helpful resource materials for the course include the following.
Hoff, CSSS - Statistics 560 Lecture notes (Sakai)
Gelman and Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models
STA 610 contain a mixture of lecture and lab sessions. Mini-assessments will be provided in lab to check mastery and identify areas for additional focus.
Note: this schedule is approximate and is likely to be modified as the course progresses. Assignments are due at the beginning of class unless otherwise specified.
Date | Topic | Deliverables |
---|---|---|
August 29 | Welcome and Introductions | ANOVA warm-up (in class) |
August 31 | One Way ANOVA: Scalar and Matrix Formulations | |
September 2 | Lab: Hands-on with ANOVA | |
September 5 | MLE’s, Contrasts, Coding Schemes, and Interaction | Scientific Writing: ANOVA Results (in class) |
September 7 | Random Effects ANOVA | |
September 9 | ANOVA Lab #2 | Assignment 1 (ANOVA) Due |
September 12 | Random Effects ANOVA (continued) | |
September 14 | Bayesian Estimation | |
September 16 | Lab: Gibbs Sampling | |
September 19 | Bayesian Estimation (continued) | |
September 21 | Random Effects ANCOVA | |
September 23 | Lab: Visualizing Estimates | Assignment 2 (ANOVA) Due |
September 26 | Higher Level Multi-Level Models and Case Study 1 Introduction | |
September 28 | Linear Mixed Effects Models - Intro | |
September 30 | Lab: Case Study 1 | |
October 3 | Exam 1 (in class) | Exam 1 (in class) |
October 5 | Linear Mixed Effects Models - Continued | |
October 7 | Lab: Help, I’m Behind! Hands-on Analysis and Q&A | Case Study 1 Write-up Due |
October 10 | Fall break | |
October 12 | Diagnostics and Influence Measures | |
October 14 | Lab: Longitudinal Data | |
October 17 | Bayesian Linear Mixed Effects Model for Longitudinal Data | |
October 19 | Generalized Linear Mixed Effects Models (GLMMs) | |
October 21 | Lab: Implementing Bayesian GLMMs in R-Stan | Assignment 3 (GLMM) Due |
October 24 | GLMMs - continued | |
October 26 | Some applications and extensions of GLMMs | |
October 28 | Lab: Hierarchical Centering | |
October 31 | Crossed/Non-Nested Random Effects, Case Study 2 Introduction | |
November 2 | Application: Election Prediction | |
November 4 | Lab: Who Votes? | Assignment 4 (GLMM) Due |
November 7 | Measurement Error | |
November 9 | Missing Data | |
November 11 | Lab: Missing data exercise | |
November 14 | Kernels/splines and inducing non-linearity | |
November 16 | Application: Meta Analysis | |
November 18 | Lab: Capturing non-linearities | |
November 21 | Multilevel Categorical Outcomes | Case Study 2 Write-up Due |
November 23 | Thanksgiving break | |
November 25 | Thanksgiving break | |
November 28 | Exam Review | |
November 30 | Exam 2 (in class) | Exam 2 (in class) |
December 2 | Lab: Make up day + misc help |