Improving the Statistical Power and Reliability of Research Using Amazon Mechanical Turk
讨论了使用亚马逊土耳其机器人进行实验研究时面临的统计功效和可靠性挑战，并提出了利用该平台优势的应对建议，对使用在线平台的博士生、研究者及审稿编辑有参考价值。
SYNOPSIS Amazon Mechanical Turk (MTurk) is an increasingly popular source of experimental participants due to its convenience and low cost (relative to traditional laboratories). However, MTurk presents challenges related to statistical power and reliability. These challenges are not unique to MTurk, but are more prevalent than in research conducted with other participant pools. In this paper I discuss several reasons why research conducted with MTurk may face additional power and reliability challenges. I then present suggestions for dealing with these challenges, taking advantage of the comparative strengths of MTurk. The discussion should be of interest to Ph.D. students and other researchers considering using MTurk or other online platforms as a source of experimental participants as well as to reviewers and editors who are considering quality control standards for research conducted with this participant pool. JEL Classifications: M40; M41; M42; C18; C90; C91.