Review of Best Practice Recommendations for Ensuring High Quality Data with Amazon’s Mechanical Turk

Author:

Bauer BrianORCID,Larsen Kristy L.,Caulfield Nicole,Elder Domynic,Jordan Sara,Capron Daniel

Abstract

Our ability to make scientific progress is dependent upon our interpretation of data. Thus, analyzing only those data that are an honest representation of a sample is imperative for drawing accurate conclusions that allow for robust, generalizable, and replicable scientific findings. Unfortunately, a consistent line of evidence indicates the presence of inattentive/careless responders who provide low-quality data in surveys, especially on popular online crowdsourcing platforms such as Amazon’s Mechanical Turk (MTurk). Yet, the majority of psychological studies using surveys only conduct outlier detection analyses to remove problematic data. Without carefully examining the possibility of low-quality data in a sample, researchers risk promoting inaccurate conclusions that interfere with scientific progress. Given that knowledge about data screening methods and optimal online data collection procedures are scattered across disparate disciplines, the dearth of psychological studies using more rigorous methodologies to prevent and detect low-quality data is likely due to inconvenience, not maleficence. Thus, this review provides up-to-date recommendations for best practices in collecting online data and data screening methods. In addition, this article includes resources for worked examples for each screening method, a collection of recommended measures, and a preregistration template for implementing these recommendations.

Publisher

Center for Open Science

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3