Disentangling Bias and Variance in Election Polls

By Houshmand Shirani-mehr, David M. Rothschild, Sharad Goel, Andrew Gelman. 2018

85 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Political Science and International Relations, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/ed97b0e069f0f20b011a9bfa42446ca6d588bd89

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Andrew Gelman
2. Jonah Gabry
3. Daniel P. Simpson
4. Bob Carpenter
5. Aki Vehtari
6. Yuling Yao
7. Paul-Christian Burkner
8. Michael Scharkow

In Political Science and International Relations

1. Andrew Gelman

In Sociology and Political Science

1. Andrew Gelman
2. Xiao-Li Meng
3. Justin T. Pickett
4. Andrew J. Thompson

Citations in the corpus

• Bayesian Workflow (2020, methodology): “For example, in election forecasting, our model for polls includes terms for nonsampling error for individual polls and for polling averages, following Shirani-Mehr et al. (2018).”