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中文摘要
翻译
项目总结 密集的纵向行为网络(ILHBN)提供了前所未有的 推进和塑造健康行为科学和技术未来格局的机会 相关干预实践。集约化纵向研究创新中心 (CIILS)位于宾夕法尼亚州立大学(宾夕法尼亚州立大学),汇集了 跨学科团队协同支持和协调跨领域的研究活动 多样化的预期U01项目组合,以实现网络的更大目标 持续创新使用集约纵向数据(ILD)和相关数据 方法研究健康行为变化及健康相关干预措施。这个 拟议的行政补充将为CIILS提供一年的延期,包括 继续协调ILHBN活动的资金,并加强以下方面的集体影响 该网络通过实现以下目标来实现。首先,我们将继续管理所有 ILHBN的行政和监管方面。第二,我们将与 U01网站协同推进健康行为理论和科学 通过帮助编辑、整理、协调、共享和分析数据来干预实践 汇集多个父项目以解决常见的交叉研究问题 利息。第三,我们将领导一个交叉研究项目,以探索缺失的数据模式和 自报告情感和基于传感器的运动数据的建模方法。
英文摘要
PROJECT SUMMARY The Intensive Longitudinal Behavior Network (ILHBN) provides an unprecedented opportunity to advance and shape the future landscape of health behavior science and related intervention practice. The Center for Innovation in Intensive Longitudinal Studies (CIILS), housed at the Pennsylvania State University (Penn State), brings together an interdisciplinary team to synergistically support and coordinate research activities across a diverse portfolio of anticipated U01 projects to accomplish the Network's larger goal of sustained innovation in the use of intensive longitudinal data (ILD) and associated methods in the study of health behavior change and health-related interventions. The proposed administrative supplement will provide CIILS with a one-year extension with funds to continue coordination of ILHBN activities, and enhance the collective impacts of the Network by accomplishing the following aims. First, we will continue to manage all administrative and regulatory aspects of ILHBN. Second, we will collaborate with the U01 sites to synergistically advance the science of health behavior theory and intervention practice by helping to compile, curate, harmonize, share, and analyze data pooled across several parent projects to address common cross-study questions of interest. Third, we will lead a cross-study project to explore missing data patterns and modeling methods for self-report affect and sensor-based movement data.
期刊论文(11)
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会议论文
DOI: 10.1080/00273171.2019.1566050
发表时间: 2019-09-03
期刊: MULTIVARIATE BEHAVIORAL RESEARCH
影响因子: 3.8
作者: [Chow, Sy-Miin]
通讯作者: Chow, Sy-Miin
Estimation of nonlinear mixed-effects continuous-time models using the continuous-discrete extended Kalman filter.
使用连续离散扩展卡尔曼滤波器估计非线性混合效应连续时间模型。
DOI: 10.1111/bmsp.12318
发表时间: 2023
期刊: The British journal of mathematical and statistical psychology
影响因子: --
作者: [Ou,Lu, Hunter,MichaelD, Lu,Zhaohua, Stifter,CynthiaA, Chow,Sy-Miin]
通讯作者: Chow,Sy-Miin
Evaluating Discrete Time Methods for Subgrouping Continuous Processes
评估连续过程分组的离散时间方法
DOI: 10.1080/00273171.2023.2235685
发表时间: 2023
期刊: Multivariate Behavioral Research
影响因子: 3.8
作者: [Park, Jonathan J., Fisher, Zachary F., Chow, Sy-Miin, Molenaar, Peter C.]
通讯作者: Molenaar, Peter C.
On Subgrouping Continuous Processes in Discrete Time
关于离散时间连续过程的子组
DOI: 10.1080/00273171.2022.2160957
发表时间: 2023
期刊: Multivariate Behavioral Research
影响因子: 3.8
作者: [Park, Jonathan J., Fisher, Zachary, Chow, Sy-Miin, Molenaar, Peter C.]
通讯作者: Molenaar, Peter C.
共 10 条
    The Center for Innovation in Intensive Longitudinal Studies (CIILS)
    海外基金