Southwestern University of Finance and Economics, Chengdu, China.
PLoS One. 2021 Mar 25;16(3):e0248805. doi: 10.1371/journal.pone.0248805. eCollection 2021.
To improve interpersonal comparability of self-reported measures, anchoring vignettes are increasingly collected in surveys and modeled as the hierarchical ordered probit (HOPIT) model. This paper-based on the idea of psychological distance-relaxes the assumption of vignette equivalence in the HOPIT by allowing for heteroscedasticity in respondents' perceptions of vignettes. Particularly, we assume that respondents who are more similar to a vignette are more familiar with the condition described and therefore are capable of forming a more precise perception of the vignette. We show evidence in favor of this extended HOPIT through Monte Carlo simulations and an application concerning self-reported vision difficulty from the WHO Study on Global Aging and Adult Health (SAGE).
为了提高自我报告测量的人际可比性,越来越多的锚定情景被收集在调查中,并被建模为层次有序概率(HOPIT)模型。本文基于心理距离的思想,通过允许受访者对情景的看法存在异方差,放宽了 HOPIT 中情景等价的假设。具体来说,我们假设与情景越相似的受访者对所描述的情况越熟悉,因此能够更准确地感知情景。我们通过蒙特卡罗模拟和一个关于世界卫生组织全球老龄化和成人健康研究(SAGE)中自我报告视力困难的应用来证明这个扩展的 HOPIT 的有效性。