The Differential Time-Varying Effect Model (DTVEM): A tool for diagnosing and modeling time lags in intensive longitudinal data.

The Differential Time-Varying Effect Model (DTVEM): A tool for diagnosing and modeling time lags in intensive longitudinal data.
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差异时变效应模型(DTVEM):用于密集纵向数据中诊断和建模时间滞后的工具。

DOI:
10.3758/s13428-018-1101-0
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发表时间:
2019-03
影响因子:
5.4
通讯作者:
Newman MG
Newman MG
中科院分区:
心理学2区
文献类型:
--
作者:
Jacobson NC;Chow SM;Newman MG

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随着最近密集纵向设计的增长以及对分析此类数据的方法的相应需求,对用户友好的分析工具的需求从未如此迫切,这些工具可以识别和估计密集纵向数据中的最佳时间滞后。用于确定单变量和多变量多受试者时间序列内最佳时间滞后的可用标准探索方法在群体(即群体)水平上的作用严重不足。我们描述了一种混合探索性验证工具,本文称为微分时变效应模型(DTVEM),其具有方便的用户可访问功能来识别最佳时间滞后并在状态空间框架内估计这些滞后。来自实证生态瞬时评估研究的数据用于证明所提出的工具在确定研究一组本科生紧张和心率之间联系的最佳时间延迟方面的效用。通过模拟研究,我们说明了 DTVEM 在识别多主体、缺失时间序列数据中的最佳滞后结构方面的有效性,以及与其他现有方法相比,其作为混合探索性验证方法的优点和局限性。
With the recent growth in intensive longitudinal designs and corresponding demand for methods to analyze such data, there has never been a more pressing need for user-friendly analytic tools that can identify and estimate optimal time lags in intensive longitudinal data. Available standard exploratory methods to identify optimal time lags within univariate and multivariate multiple subject time series are greatly under-powered at the group (i.e., population) level. We describe a hybrid exploratory-confirmatory tool, referred to herein as the Differential Time-Varying Effect Model (DTVEM), which features a convenient user-accessible function to identify optimal time lags and estimate these lags within a state-space framework. Data from an empirical ecological momentary assessment study are used to demonstrate the utility of the proposed tool in identifying the optimal time lag for studying the linkages between nervousness and heart rate in a group of undergraduate students. Using a simulation study, we illustrate the effectiveness of DTVEM in identifying optimal lag structures in multiple-subject, time series data with missingness, as well as its strengths and limitations as a hybrid exploratory-confirmatory approach compared to other existing approaches.
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