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  • Search Term: "R. Michael Alvarez"

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Improving the quality of surveys: a Q&A with Daniel Oberski

By R. Michael Alvarez
Empirical work in political science must be based on strong scientifically-accurate measurements. However, the problem of measurement error hasn’t been sufficiently addressed. Recently, Willem Saris and Daniel Oberski’s Survey Quality Prediction software wasdeveloped to better predict reliability and method variance, and is receiving the 2014 Warren J. Mitofsky Innovators Award from the American Association for Public Opinion Research.

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Reading the tea leaves: a Q&A with Costas Panagopoulos

By R. Michael Alvarez In a matter of months, federal elections in the United States will enter full-swing. I recently asked Costas Panagopoulos, a professor at Fordham University and an expert on political campaigns, a few questions about the important elections recently conducted in the United States and what we might learn from those recent campaigns. […]

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Polling accuracy: a Q&A with Kai Arzheimer and Jocelyn Evans

By R. Michael Alvarez
Polling data is ubiquitous in today’s world, but it is is often difficult to easily understand the accuracy of polls. In a recent paper published in Political Analysis, Kai Arzheimer and Jocelyn Evans developed a new methodology for assessing the accuracy of polls in multiparty and multi-candidate elections.

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Is big data a big deal in political science?

By Michael Alvarez
Not a day passes when I don’t see something in the news about big data. Sometimes the stories will be about some interesting new big data application. For example I recently read about the WeatherSignal app that is collecting weather data from smartphones. And of course there has been a lot in the news lately about the big data and privacy,

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Argentina’s elections: A Q&A

In anticipation of Argentina’s mid-term elections to be held on Sunday, 27 October 2013, Political Analysis co-editor R. Michael Alvarez (Caltech) discussed some of the most important things that we need to know about this contest with Francisco Cantu (University of Houston) and Sebastian Saiegh (UCSD).

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