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Times are changing, bias isn't: A meta-meta-analysis on publication bias detection practices, prevalence rates, and predictors in industrial/organizational psychology.
Journal of Applied Psychology ( IF 11.802 ) Pub Date : 2021-12-30 , DOI: 10.1037/apl0000991
Magdalena Siegel 1 , Junia Sophia Nur Eder 1 , Jelte M Wicherts 2 , Jakob Pietschnig 1
Affiliation  

Effect misestimations plague Psychological Science, but advances in the identification of dissemination biases in general and publication bias in particular have helped in dealing with biased effects in the literature. However, the application of publication bias detection methods appears to be not equally prevalent across subdisciplines. It has been suggested that particularly in I/O Psychology, appropriate publication bias detection methods are underused. In this meta-meta-analysis, we present prevalence estimates, predictors, and time trends of publication bias in 128 meta-analyses that were published in the Journal of Applied Psychology (7,263 effect sizes, 3,000,000 + participants). Moreover, we reanalyzed data of 87 meta-analyses and applied nine standard and more modern publication bias detection methods. We show that (a) the bias detection method applications are underused (only 41% of meta-analyses use at least one method) but have increased in recent years, (b) those meta-analyses that apply such methods now use more, but mostly inappropriate methods, and (c) the prevalence of potential publication bias is concerning but mostly remains undetected. Although our results indicate somewhat of a trend toward higher bias awareness, they substantiate concerns about potential publication bias in I/O Psychology, warranting increased researcher awareness about appropriate and state-of-the-art bias detection and triangulation. Embracing open science practices such as data sharing or study preregistration is needed to raise reproducibility and ultimately strengthen Psychological Science in general and I/O Psychology in particular. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

中文翻译:

时代在变,偏见却没有:对工业/组织心理学中出版偏见检测实践、流行率和预测因素的元分析。

效应错误估计困扰着心理科学,但在识别一般传播偏差和特别是出版偏差方面取得的进展有助于处理文献中的偏差效应。然而,发表偏倚检测方法的应用似乎在各个子学科中并不同样普遍。有人建议,特别是在 I/O 心理学中,适当的发表偏倚检测方法并未得到充分利用。在这项荟萃分析中,我们展示了发表在《应用心理学杂志》上的 128 项荟萃分析(7,263 个效应量,3,000,000 多名参与者)中发表偏倚的患病率估计、预测因素和时间趋势。此外,我们重新分析了 87 项荟萃分析的数据,并应用了九种标准和更现代的发表偏倚检测方法。我们表明,(a) 偏差检测方法的应用未得到充分利用(只有 41% 的荟萃分析至少使用一种方法),但近年来有所增加,(b) 应用此类方法的荟萃分析现在使用更多,但大多是不适当的方法,(c) 潜在发表偏倚的普遍存在令人担忧,但大多仍未被发现。尽管我们的结果表明存在更高的偏见意识的趋势,但它们证实了对 I/O 心理学中潜在的发表偏见的担忧,保证了研究人员对适当和最先进的偏见检测和三角测量的认识的提高。需要采用数据共享或研究预注册等开放科学实践来提高可重复性,并最终加强一般心理科学,特别是 I/O 心理学。(PsycInfo 数据库记录 (c) 2022 APA,保留所有权利)。
更新日期:2021-12-30
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