Follow the instructions for assignments here
| Assignment | Due date | Peer review | Self corrections |
|---|---|---|---|
| Assignment 1 | Thu, Apr 13, 2017 13:30 | ||
| Assignment 2 | Tue, Apr 25, 2017 13:30 | ||
| Assignment 3 | Tue, May 09, 2017 14:30 | ||
| Assignment 4 | Thu, May 25, 2017 13:30 | Sat, Jun 03, 2017 13:30 | Fri, Jun 09, 2017 17:00 |
Readings before class:
"The Golem of Prague", Statistical Rethinking, Ch 1.
Readings before class:
"Small Worlds and Large Worlds", Statistical Rethinking, Ch 2.
"Sampling the Imaginary", Statistical Rethinking, Ch 3.
"Probability and Inference", BDA, Ch 1.
Readings before class:
"Linear Models", Statistical Rethinking, Ch 4.
"Introduction to Single-Parameter Models", BDA, Ch 2.
Readings before class:
"Multivariate Linear Models", Statistical Rethinking, Ch 5.
"Interactions", Statistical Rethinking, Ch 7.
In class:
Worked through code in an example based on Introduction to Stan with Linear Regression
The Statistical Rethinking chapter provides some of the theoretical background on MCMC sampling. The various readings about Stan and rstan all provide some overview and instructions for Stan models, though all assume at various parts knowledge that I don't expect all (if any) students to have. They are often written for someone who is already familiar with Bayesian statistics and software. The best strategy is to scan them, and if there are parts that assume knowledge you aren't familiar with, don't worry about it. Reading the introduction to the Stan Documentation is as much about getting familiar with what's in this documentation as anything else. The Stan Modeling Language Documentation includes both extensive documentation about the language and functions and many example models.
Readings before class:
"Introduction" in Stan Modeling Language User’s Guide and Reference Manual
"Regression Models" in Stan Modeling Language User’s Guide and Reference Manual
"Markov Chain Monte Carlo", Statistical Rethinking, Ch 8.
Optional readings after class:
Readings before class:
"Markov Chain Monte Carlo", Statistical Rethinking, Ch 8.
Readings before class:
"Counting and Classification", Statistical Rethinking, Ch 10.
"Generalized Linear Models", BDA, Ch 12.
Optional readings after class:
"Regression Models", Stan Reference
Gelman, Andrew. 2008. "A weakly informative default prior distribution for logistic and other regression models](https://projecteuclid.org/euclid.aoas/1231424214)"
Rainey, Carlisle. 2016. "Dealing with Separation in Logistic Regression Models"
Readings before class:
Statistical Rethinking Ch 12. "Multilevel Models"
Statistical Rethinking Ch 13. "Adventures in Covariance"
Readings before class:
Statistical Rethinking Ch 14. "Missing Data"
Clinton, Jackman, and Rivers. 2004. "The Statistical Analysis of Roll Call Data" American Political Science Review. doi:10.1017/S0003055404001194.
Clinton, Jackman, and Rivers. 2001. "Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference, and Model Checking"
Bafumi, Gelman, Park, and Kaplan. 2005. "Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation" Political Analysis 10.1093/pan/mpi010.
Robert Myles McDonnell, Bayesian Ideal Points with Stan in R
Rich Farouni. 2015. "Fitting a Bayesian Factor Analysis Model in Stan" link
In class:
Readings before class:
Treier and Jackman. 2004. "Democracy as a Latent Variable." American Journal of Political Science [doi:10.1111/j.1540-5907.2007.00308.x]http://onlinelibrary.wiley.com/doi/10.1111/j.1540-5907.2007.00308.x](https://dx.doi.org/10.1111/j.1540-5907.2007.00308.x)
Pemstein. Meserve, and Melton. 2010. "Democratic Compromise: A Latent Variable Analysis of Ten Measures of Regime Type" Political Analysis doi:10.1093/pan/mpq020. Also see the associated website for Unified Democracy Scores and the subsequent Varieties of Democracy project.
In class:
Continue ideal point example.
Readings before class:
West. 2013. "Bayesian Dynamic Modeling" PDF
Dynamic Bayesian Forecasting of Presidential Elections in the States
Pierre-Antoine Kremp. "State and National Poll Aggregation" URL and GitHub.
Jackman. 2005. "Pooling the Polls over an Election Campaign" doi:10.1080/1036114050030247
In class:
NO CLASS
Readings before class:
Fariss. 2014. "Respect for Human Rights has Improved Over Time: Modeling the Changing Standard of Accountability" American Political Science Review
Schnakenberg and Fariss. 2014. "Dynamic Patterns of Human Rights Practices" Political Science Research and Methods
In class:
Work through polling data example.