Commentary to MARP: how to increase the robustness of survey studies

IF 3.6 3区 哲学 0 RELIGION Religion Brain & Behavior Pub Date : 2022-07-06 DOI:10.1080/2153599X.2022.2070257
Chris-Gabriel Islam, J. Lorenz
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引用次数: 1

Abstract

This comment aims at one attribute that leaves room for improvement of the generally well-thought-out many-analysts-religion-project (MARP) approach (Hoogeveen, et al., 2022): All teams used only one data set. We present our analyses based on an extended database, referring to literature on replicability and the relationship between religiosity and well-being before ending with recommendations for future projects of this kind. The MARP approach will give new insights into the challenge of replicability of research fi ndings inherent to every project that is carried out by only one researcher or research group. What remains is the problem of drawing reliable conclusions based on only one data set. One data set might always be prone to selection bias and it might lack representativity as well as potentially important variables that were not collected. In order to argue for a robust e ff ect between well-being and religiosity, the e ff ect should be still measurable when interchanging the collected data with other survey data or when adding additional variables, including from other data sets, in order to avoid omitted variable bias. In economics, Clemens (2017) presents a classi fi cation for replication studies, which distinguishes among four types of replication and robustness checks: veri fi cation, reproduction, reanalysis, and extension (see Table 1). If we classify the MARP approach according to this classi fi cation scheme, we would consider it a robustness check of the reanalysis type. The participating researchers used the same population, although they speci fi ed their samples and analytical models di ff erently. To achieve a replication of the studies within MARP, any researcher could use the published analysis scripts and repeat the analyses with the same or another sample.
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MARP评论:如何增加调查研究的稳健性
这一评论针对的是一个属性,该属性为经过深思熟虑的许多分析师-宗教-项目(MARP)方法(hoogevenen等人,2022)留下了改进的空间:所有团队只使用一个数据集。我们基于一个扩展的数据库提出了我们的分析,参考了关于可复制性和宗教信仰与幸福之间关系的文献,最后提出了对未来此类项目的建议。MARP方法将为研究结果的可复制性挑战提供新的见解,这些研究结果固有地存在于仅由一个研究人员或研究小组进行的每个项目中。剩下的问题是仅根据一组数据得出可靠的结论。一个数据集可能总是倾向于选择偏差,它可能缺乏代表性以及未收集的潜在重要变量。为了证明幸福感和宗教信仰之间存在强大的效应,在将收集的数据与其他调查数据交换或添加其他变量(包括来自其他数据集的变量)时,效应仍然应该是可测量的,以避免遗漏的变量偏差。在经济学中,Clemens(2017)提出了复制研究的分类,区分了四种类型的复制和稳健性检查:验证、复制、再分析和扩展(见表1)。如果我们根据这种分类方案对MARP方法进行分类,我们会认为它是一种再分析类型的稳健性检查。参与研究的研究人员使用了相同的人群,尽管他们指定的样本和分析模型不同。为了在MARP中实现研究的复制,任何研究人员都可以使用已发表的分析脚本,并对相同或另一个样本重复分析。
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来源期刊
CiteScore
3.00
自引率
13.60%
发文量
93
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