Andreas B Neubauer, Peter Koval, Michael J Zyphur, Ellen L Hamaker
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引用次数: 0
摘要
密集的纵向设计使研究人员能够研究日常生活中心理过程的动态。然而,由于这些方法通常是观察性的,它们不允许强有力的因果推论。一个有希望的解决方案是在密集的纵向设计中纳入(微观)随机干预措施,以揭示人体内(Wp)的因果效应。然而,目前尚不清楚所产生的Wp因果效应是否(或如何)转化为结果的人与人之间(Bp)差异。在这项工作中,我们通过分析和模拟数据表明,如果没有调节这种跨层转换的抵消力,那么Wp因果效应会转化为Bp差异。我们在此考虑的三种可能的抵消力量是:(a)情境效应,(b)相关随机效应,以及(c)跨层交互作用。我们使用一项为期10天的微随机正念干预研究(n = 91)的经验数据来说明这些原则,在该研究中,参与者在每个情况下随机完成治疗或控制任务。最后,我们提出了在密集的纵向设计中设计微随机实验的建议,以及对这些设计产生的数据进行统计分析。(PsycInfo Database Record (c) 2025 APA,版权所有)。
Experiments in daily life: When causal within-person effects do (not) translate into between-person differences.
Intensive longitudinal designs allow researchers to study the dynamics of psychological processes in daily life. Yet, because these methods are usually observational, they do not allow strong causal inferences. A promising solution is to incorporate (micro-)randomized interventions within intensive longitudinal designs to uncover within-person (Wp) causal effects. However, it remains unclear whether (or how) the resulting Wp causal effects translate into between-person (Bp) differences in outcomes. In this work, we show analytically and using simulated data that Wp causal effects translate into Bp differences if there are no counteracting forces that modulate this cross-level translation. Three possible counteracting forces that we consider here are (a) contextual effects, (b) correlated random effects, and (c) cross-level interactions. We illustrate these principles using empirical data from a 10-day microrandomized mindfulness intervention study (n = 91), in which participants were randomized to complete a treatment or control task at each occasion. We conclude by providing recommendations regarding the design of microrandomized experiments in intensive longitudinal designs, as well as the statistical analyses of data resulting from these designs. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
期刊介绍:
Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.