Online Survey Quality, PoliSciData.com Special Edition

About This Page

This page features political science articles examining 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.

Replication Data from Peer-Reviewed Studies

PSR&M Recruiting Large Online Samples in the United States and India: Facebook, Mechanical Turk and QualtricsTaylor Boas et al. (2020). R files: 16, text files: 9, datasets: 14, PDF files: 6, LaTeX files: 1, HTML files: 2.

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PSR&M Generalizing from Survey Experiments Conducted on Mechanical Turk: A Replication ApproachAlexander Coppock (2019). R files: 7, HTML files: 6, datasets: 4, text files: 1.

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AJPS No Harm in Checking: Using Factual Manipulation Checks to Assess Attentiveness in ExperimentsJohn V. Kane et al. (2019). Stata files: 2, PDF files: 1, datasets: 8, text files: 1.

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R&P The Face of Internet Recruitment: Evaluating the Labor Markets of Online Crowdsourcing Platforms in ChinaXiaojun Li et al. (2018). R files: 1, datasets: 6, text files: 4.

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PSR&M Using Screeners to Measure Respondent Attention on Self-Administered Surveys: Which Items and How Many?Christopher Warshaw et al. (2021). R files: 3, Stata files: 1, text files: 1, datasets: 1.

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Pol. Analysis Paying Attention to Inattentive Survey RespondentsR. Michael Alvarez et al. (2019). R files: 2, datasets: 2, text files: 1.

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Pol. Behav.Sponsorship Effects in Online SurveysHolger Kern et al. (2022). R files: 6, text files: 1, datasets: 5.

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Pol. Analysis Racing the Clock: Using Response Time As a Proxy for Attentiveness on Self-Administered SurveysBlair Read et al. (2022). archives: 1.

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AJPS Separating the Shirkers from the Workers? Making Sure Respondents Pay Attention on Self-Administered SurveysAdam Berinsky et al. (2014). Stata files: 3, datasets: 8, text files: 3.

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PSR&M The Shape of and Solutions to the MTurk Quality CrisisRyan Kennedy et al. (2020). R files: 1, Stata files: 4, images: 12, PDF files: 4, datasets: 40, text files: 1.

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Pol. Analysis Crowdsourcing Reliable Local DataMirya Holman et al. (2020). archives: 1.

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APSR Testing Social Science Network Theories With Online Network Data: An Evaluation of External ValidityJames Bisbee et al. (2017). R files: 8, Stata files: 6, PDF files: 16, datasets: 19, LaTeX files: 4, text files: 6.

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Pol. Analysis A Note on Dropping Experimental Subjects Who Fail a Manipulation CheckPeter M. Aronow et al. (2019). archives: 1.

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Pol. Analysis A Text-As-Data Approach for Using Open-Ended Responses As Manipulation ChecksJeffrey Ziegler (2022). R files: 3, other files: 1, PDF files: 17, images: 1, LaTeX files: 9, text files: 1.

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Also see Journal Data Archives | Author Replication Data

Watch & Learn

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From Professor Kramer (35:20).

Quantitative Survey Design With Qualtrics for MTurk

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From the Pew Research Center (4:25).

How Did the Pew Research Center Identify Twitter Bots?

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