Curran Patrick J, Georgeson A R, Bauer Daniel J, Hussong Andrea M
University of North Carolina, USA.
Int J Behav Dev. 2021 Jan 1;45(1):40-50. doi: 10.1177/0165025419896620. Epub 2020 Jan 9.
Conducting valid and reliable empirical research in the prevention sciences is an inherently difficult and challenging task. Chief among these is the need to obtain numerical scores of underlying theoretical constructs for use in subsequent analysis. This challenge is further exacerbated by the increasingly common need to consider multiple reporter assessments, particularly when using integrative data analysis to fit models to data that have been pooled across two or more independent samples. The current paper uses both simulated and real data to examine the utility of a recently proposed psychometric model for multiple reporter data called the trifactor model (TFM) in settings that might be commonly found in prevention research. Results suggest that numerical scores obtained using the TFM are superior to more traditional methods, particularly when pooling samples that contribute different reporter perspectives.
在预防科学领域开展有效且可靠的实证研究，本质上是一项艰巨且具有挑战性的任务。其中最主要的困难在于需要获取潜在理论构念的数值分数，以便用于后续分析。而考虑多个报告者评估的需求日益普遍，这一挑战进一步加剧，特别是在使用整合数据分析来拟合跨两个或更多独立样本汇总的数据模型时。本文使用模拟数据和真实数据，检验了一种最近提出的用于多报告者数据的心理测量模型——三因素模型（TFM）在预防研究常见场景中的效用。结果表明，使用TFM获得的数值分数优于更传统的方法，尤其是在汇总提供不同报告者视角的样本时。
