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关于在 T 值较小时使用约束四阶潜在差分方程模型的说明。

A Note on the Usefulness of Constrained Fourth-Order Latent Differential Equation Models in the Case of Small T.

机构信息

Department of Psychology, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany.

Department of Psychology, University of Virginia, Gilmer Hall Room 102, Charlottesville, VA, 22903, USA.

出版信息

Psychometrika. 2020 Dec;85(4):1016-1027. doi: 10.1007/s11336-020-09738-x. Epub 2020 Dec 20.

Abstract

Constrained fourth-order latent differential equation (FOLDE) models have been proposed (e.g., Boker et al. 2020) as alternative to second-order latent differential equation (SOLDE) models to estimate second-order linear differential equation systems such as the damped linear oscillator model. When, however, only a relatively small number of measurement occasions T are available (i.e., [Formula: see text]), the recommendation of which model to use is not clear (Boker et al. 2020). Based on a data set, which consists of [Formula: see text] observations of daily stress for [Formula: see text] individuals, we illustrate that FOLDE can help to choose an embedding dimension, even in the case of a small T. This is of great importance, as parameter estimates depend on the embedding dimension as well as on the latent differential equations model. Consequently, the wavelength as quantity of potential substantive interest may vary considerably. We extend the modeling approaches used in past research by including multiple subjects, by accounting for individual differences in equilibrium, and by including multiple instead of one single observed indicator.

摘要

已经提出了约束四阶潜在微分方程 (FOLDE) 模型(例如,Boker 等人,2020 年),作为二阶潜在微分方程 (SOLDE) 模型的替代方法,以估计二阶线性微分方程系统,如阻尼线性振荡器模型。然而,当仅有相对较少的测量次数 T 可用时(即,[公式:见文本]),哪种模型更适用尚不清楚(Boker 等人,2020 年)。基于一个数据集,该数据集包含[公式:见文本]个个体每日压力的观测值,我们举例说明即使在 T 较小的情况下,FOLDE 也可以帮助选择嵌入维度。这非常重要,因为参数估计取决于嵌入维度以及潜在微分方程模型。因此,作为潜在实质性兴趣的数量的波长可能会有很大差异。我们通过包含多个主体、考虑平衡的个体差异以及包含多个而不是一个单个观测指标来扩展过去研究中使用的建模方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91af/7826318/251ea34b56d8/11336_2020_9738_Fig1_HTML.jpg

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