Using fixed and random effects models for panel data in Python
Identifying causal relationships from observational data is not easy. Still, researchers are often interested in examining the effects of policy changes.
A behind-the-scenes blog about research methods at Pew Research Center.
For our latest research findings, visit pewresearch.org.
All Decoded publications
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5 tips for writing about polls
There are some simple guidelines writers can follow to minimize the risk of readers misunderstanding or misinterpreting survey findings.
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How we check numbers and facts at Pew Research Center
All of the material we release goes through a rigorous verification process we call a “number check.”
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Exploring the link between European political parties’ ideology and their popularity on Twitter
It can be hard to determine whether parties near the ends of the ideology scale are more popular on the platform than moderate parties.
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Interpreting and validating topic models
Understanding the exact meaning of a set of words requires an intimate understanding of how the words are used in your data and the meaning they’re likely intended to convey in context.
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Lessons learned from more than 20 years of asking about Americans’ online habits
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.
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Using tidyverse tools with Pew Research Center survey data in R
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.
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What happens when a survey estimate doesn’t match a known benchmark
From time to time, data collected through surveys doesn’t match sources that are widely acknowledged as accurate.
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Overcoming the limitations of topic models with a semi-supervised approach
In this post, I’ll show how to overcome some of challenges that arise with topic modeling with what’s known as a “semi-supervised” approach.
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Crowdsourcing a video coding project can be as effective as using trained research assistants
Measuring the content and meaning of videos is an important research goal for social scientists, but the tools for analyzing them at scale lag behind new advances.
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- Demographic Research (7)
- Communicating Findings (8)
- Online Surveys (2)
- Voter Files (4)
- Survey Methods (33)
- Coding How-To (18)
- Economic Research (4)
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About Decoded
A behind-the-scenes blog about research methods at Pew Research Center.
For our latest research findings, visit pewresearch.org.
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