The construct of psychophysiological reactivity: Statistical and psychometric issues
The construct of psychophysiological reactivity: Statistical and psychometric issues
复制标题
DOI：
10.1016/j.dr.2012.10.002
复制
发表时间：
2013-03-01
影响因子：
6.6
通讯作者：
Obradovic, Jelena
中科院分区：
文献类型：
--
作者：
Burt, Keith B.;Obradovic, Jelena
本文的目的是回顾影响心理生理反应性研究的主要统计和心理测量学问题，并讨论它们对应用发展研究者的启示。我们首先介绍了传统的方法，如观察差异得分（DS）和观察残差得分（RS），包括对两个相关工作机构的经典和最新研究的回顾：变化测量和初值定律。其次，我们回顾了几种潜在变量模型：潜在差异评分（LDS）模型、潜在残差评分（LRS）模型、潜在状态-特质（LST）模型和潜在生长曲线（LGC）模型。最后，我们根据心理生理学项目的关键阶段为应用研究人员提供了广泛的指导方针：研究计划，数据分析和结果报告。我们的建议强调需要(1)增加对观察变量中测量误差的普遍性质的关注，以及尽可能使用潜在变量模型的重要性；(2)增加与反应性构建相关的理论规范，特别是在更广泛的变量系统中基线唤醒和随时间变化之间的区别。(C) 2012爱思唯尔公司版权所有。
The purpose of this paper is to review major statistical and psychometric issues impacting the study of psychophysiological reactivity and discuss their implications for applied developmental researchers. We first cover traditional approaches such as the observed difference score (DS) and the observed residual score (RS), including a review of classic and recent research on their reliability and validity from two related bodies of work: the measurement of change and the Law of Initial Values. Second, we review several types of latent variable modeling in this context: latent difference score (LDS) models, latent residual score (LRS) models, latent state-trait (LST) models, and latent growth curve (LGC) models. Finally, we provide broad guidelines for applied researchers broken down by key stages of a psychophysiological project: study planning, data analysis, and reporting of results. Our recommendations highlight the need for (1) increased attention to the ubiquitous nature of measurement error in observed variables and the importance of employing latent variable models when possible, and (2) increased specification of theories relating to the construct of reactivity, especially in regards to the distinction between baseline arousal and change over time in broader systems of variables. (C) 2012 Elsevier Inc. All rights reserved.