SPECIAL FEATURE: Online Survey Quality

About This Feature

This special feature of Political Science Data examines the quality and reliability of online surveys, exploring issues like sample representativeness, response bias, and data validity. Understanding these challenges is crucial for researchers and practitioners as online surveys become an increasingly common tool for gathering public opinion and behavioral data. Featured on site 2024/25.

Watch & Learn

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MTurk Research: Recommendations and Best Practices

Research presentation for GWU (5:51).

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Random Digit Dialing Vs. Registration Based Sampling

A Marist Poll Academy case study (2:30).

Replication Data from Peer-Reviewed Studies

Online Social Ties Mirror Offline Relationships: Implications for Political Science Research
Experimental Methods2017@APSR 8 R files 6 Stata files 19 datasets Dataverse
Turn Open-Ended Answers Into Continuous Attention Checks
Survey Experiments2022@Pol. An.3 R files Dataverse
Attention Not Enough? Why Single Survey Screeners Fall Short in Political Studies
2014@AJPS 3 Stata files 8 datasets Dataverse
How Crowdsourcing Makes Local Government Data Accurate and Cheap
2020@Pol. An.Dataverse
Ignoring Inattentive Respondents Biases Political Surveys — Even List Experiments
Survey Data2019@Pol. An.2 R files 2 datasets Dataverse
Screeners Could Enhance Political Science Data Quality
2021@PSR&M 3 R files 1 Stata file 1 dataset Dataverse
How Do Survey Experiments on Mechanical Turk Generalize? New Replication Evidence Provides Insights.
2019@PSR&M 7 R files 4 datasets Dataverse
Amazon Mechanical Turk's Data Quality Crisis: New Insights into Detection
2020@PSR&M 1 R file 4 Stata files 40 datasets Dataverse
Online Recruitment in India vs. U.S.: Not All Samples Can Make Valid Inferences
2020@PSR&M 16 R files 14 datasets Dataverse
Sponsorship Shapes Survey Responses — A New Look at Online Polling Biases
Political Participation2022@Pol. Behav.6 R files 5 datasets Dataverse
Factual Checks Reveal Attention: A New Tool for Experimental Clarity
2019@AJPS 2 Stata files 8 datasets Dataverse
Dropping Manipulation-Check Failures Can Produce Serious Bias
Causal Inference manipulation checks2019@Pol. An.Dataverse
How Fast Answers Reveal Unseen Inattentiveness in Online Surveys
2022@Pol. An.Dataverse
Online Recruitment in China: Are Crowdsourced Samples Representative of Netizens?
2018@R&P 1 R file 6 datasets Dataverse

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