Exploring survey data with the pewmethods R package
This post provides tips on recoding and collapsing survey data and displaying weighted estimates of categorical variables.
A behind-the-scenes blog about research methods at Pew Research Center.
For our latest findings, visit pewresearch.org.
This post provides tips on recoding and collapsing survey data and displaying weighted estimates of categorical variables.
Our new R package contains various functions that we use in our day-to-day survey work.
Mode differences present a challenge to analyzing trends over time. While these differences can vary, there are lessons to be learned.
Identifying causal relationships from observational data is not easy. Still, researchers are often interested in examining the effects of policy changes.
From weather events to snap elections, outside developments can sometimes disrupt surveys while they are in the field.
Overall, our survey found that 13% of U.S. adult Twitter users keep their feeds private.
We’ve been asking Americans about their online news habits since the mid-1990s. Since then, the ways people get news online have changed a lot — and so have the ways we ask about it.
I wrote an introductory blog post about how to access and analyze Pew Research Center survey data with R, a free, open-source software for statistical analysis. The post showed how to perform tasks using the survey package.
Survey researchers frequently explore differences in public opinion by demographic group — how men’s views compare with those of women, for example, or how younger people compare with older people. Often, it’s also possible to look at differences by survey respondents’ geographic location. Yet, when geographic information is available in survey data, it’s not always […]
From time to time, data collected through surveys doesn’t match sources that are widely acknowledged as accurate.