Statistical modelling of vignette data in psychology.

Statistical modelling of vignette data in psychology.
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DOI:
10.1111/bjop.12577
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发表时间:
2022-11
影响因子:
4
通讯作者:
Steer, Oonagh
Steer, Oonagh
中科院分区:
心理学2区
文献类型:
--
作者:
Baguley, Thom;Dunham, Grace;Steer, Oonagh

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小插图方法广泛应用于心理学和社会科学中,以获得对多维场景或情况的响应。在收集定量数据的情况下,这对选择适当的统计模型提出了挑战。这取决于设计的微妙细节以及向参与者分配小插图。一个关键的区别是析因调查实验和实验性小插图研究之间的区别,在析因调查实验中,每个参与者从可能的小插图的整个宇宙中接收到不同的小插图分配,而实验小插图研究则放宽了这一限制。前者导致具有单个随机因子的嵌套设计,后者导致具有两个交叉随机因子的设计。此外,向参与者分配小插图可能会导致部分或不平衡的设计,以及随之而来的效率损失或兴趣效果的混叠。许多小插图研究(包括一些因子调查实验)包括小插图之间未建模的异质性,如果采用传统的回归方法,则会导致潜在的严重问题。对这些问题进行了审查,并就小插图研究的有效设计(包括将小插图分配给参与者)提出了建议。提出多层模型作为处理嵌套和交叉设计(包括不平衡和分数设计)的通用方法。这是通过一个小插图数据集来说明的,该数据集着眼于对线上和线下欺凌和骚扰的判断。
Vignette methods are widely used in psychology and the social sciences to obtain responses to multi‐dimensional scenarios or situations. Where quantitative data are collected this presents challenges to the selection of an appropriate statistical model. This depends on subtle details of the design and allocation of vignettes to participants. A key distinction is between factorial survey experiments where each participant receives a different allocation of vignettes from the full universe of possible vignettes and experimental vignette studies where this restriction is relaxed. The former leads to nested designs with a single random factor and the latter to designs with two crossed random factors. In addition, the allocation of vignettes to participants may lead to fractional or unbalanced designs and a consequent loss of efficiency or aliasing of the effects of interest. Many vignette studies (including some factorial survey experiments) include unmodeled heterogeneity between vignettes leading to potentially serious problems if traditional regression approaches are adopted. These issues are reviewed and recommendations are made for the efficient design of vignette studies including the allocation of vignettes to participants. Multilevel models are proposed as a general approach to handling nested and crossed designs including unbalanced and fractional designs. This is illustrated with a small vignette data set looking at judgements of online and offline bullying and harassment.
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