North Carolina State University Raleigh, NC, USA.
Front Psychol. 2011 Jan 21;1:220. doi: 10.3389/fpsyg.2010.00220. eCollection 2010.
Research in the social sciences often relies upon the motivation and goodwill of research participants (e.g., teachers, students) to do their best on low stakes assessments of the effects of interventions. Research participants who are unmotivated to perform well can engage in random responding on outcome measures, which can cause substantial mis-estimation of results, biasing results toward the null hypothesis. Data from a recent educational intervention study served as an example of this problem: participants identified as random responders showed substantially lower scores than other participants on tests during the study, and failed to show growth in scores from pre- to post-test, while those not engaging in random responding showed much higher scores and significant growth over time. Furthermore, the hypothesized differences across instructional method were masked when random responders were retained in the sample but were significant when removed. We remind researchers in the social sciences to screen their data for random responding in their outcome measures in order to improve the odds of detecting effects of their interventions.
社会科学研究通常依赖于研究参与者(例如教师、学生)的积极性和善意,让他们在低风险的干预效果评估中尽力而为。没有积极性表现出色的研究参与者可能会在结果测量中随机作答,这可能会导致结果的严重估计错误,使结果偏向于零假设。最近一项教育干预研究的数据就是这种问题的一个例子:在研究期间,被确定为随机应答者的参与者在测试中的得分明显低于其他参与者,并且在预测试到后测试期间没有表现出分数的增长,而没有进行随机应答的参与者的得分则高得多,并且随着时间的推移有显著增长。此外,当随机应答者保留在样本中时,假设的教学方法差异被掩盖了,但当随机应答者被剔除时,差异就变得显著了。我们提醒社会科学研究人员,要在他们的结果测量中筛查随机应答,以提高发现干预效果的几率。