Bayesian Multilevel Estimation with Poststratification: State-Level Estimates from National Polls

By David K. Park, Andrew Gelman, Joseph Bafumi. Political Analysis, 2004

445 citations recorded by the source corpus.

Subfields: Communication, Political Science and International Relations, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/2008bee9f8c2d7e41ac9c5c54489f41989a0d7ba

How researchers see this paper

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

In Communication

1. Andrew Gelman
2. A. Coppock
3. Gordon Pennycook
4. David G. Rand

In Political Science and International Relations

1. Oliver A. McClellan
2. Andrew Gelman
3. J. Goodman
4. A. Coppock
5. Ulf Böckenholt

In Strategy and Management

1. Oliver A. McClellan
2. Andrew Gelman
3. A. Coppock
4. Ulf Böckenholt

Citations in the corpus

• Crowdsourcing Consumer Research (2017, background): “…model-based poststratification can be used to statistically adjust the estimates obtained from nonrepresentative samples (Battaglia, Hoaglin, and Frankel 2013; Park, Gelman, and Bafumi 2004), and may be applied to MTurk samples (Goel, Obeng, and Rothschild 2015; Levay, Freese, and Druckman 2016).”
• Large-Scale Replication Projects in Contemporary Psychological Research (2017, background): “To place I2 in context, Pigott (2012) defines low, medium, and high heterogeneity in psychological research as I2 of 25%, 50%, and 75% respectively (see also Higgins and Thompson 2002).”
• Validating the demographic, political, psychological, and experimental results obtained from a new source of online survey respondents (2019, background): “And while it is commonplace in the popular media to conduct opinion polls using convenience samples of viewers or listeners (Kent et al., 2006), most descriptive work in political science uses explicit random sampling or reweighting techniques to target population quantities (Park et al., 2004).”