The Center for Innovation in Intensive Longitudinal Studies (CIILS)
The Center for Innovation in Intensive Longitudinal Studies (CIILS)
批准号:
10561102
负责人:
Sy-Miin Chow
金额:
$10.0万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-07-05 至 2023-08-31
关键词:
2019-nCoVAddressAdministrative PersonnelAdministrative SupplementAffectBehaviorBehavior TherapyCOVID-19 pandemicCollectionDataData CollectionData PoolingData SecurityData SetEcological momentary assessmentFundingFutureGeographic LocationsGoalsHealthHealth SciencesHealth behaviorHealth behavior changeIndividualInterventionLeadLongitudinal StudiesMeasuresMethodologyMethodsModelingMovementParentsPatient Self-ReportPatternPennsylvaniaPersonsPreventionRecording of previous eventsResearchResearch ActivityRoleScienceScientistShapesSiteTechniquesTimeTranslationsUniversitiesanalytical methodbasedata curationdata handlingdata modelingdata sharingdesigndigitalinnovationinterestmHealthmultiple data typesnovelparent projectpatient engagementresponsesecondary analysissensorsocialstudy populationsubstance usetheories
中文摘要
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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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科研奖励(0)
会议论文
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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
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.
The Differential Time-Varying Effect Model (DTVEM): A tool for diagnosing and modeling time lags in intensive longitudinal data.
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
发表时间:
2019-03
期刊:
Behavior research methods
影响因子:
5.4
作者:
[Jacobson NC, Chow SM, Newman MG]
通讯作者:
Newman MG
共 10 条
The Center for Innovation in Intensive Longitudinal Studies (CIILS)
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批准号:9788202
-
项目类别:
-
资助金额:$46.55万
-
财政年份:2018
-
负责人:Sy-Miin Chow
-
依托单位:
海外基金