What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
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Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.Depression symptoms moderate the association between emotion and communal behavior.Discrete- vs. Continuous-Time Modeling of Unequally Spaced Experience Sampling Method Data.Personalized Network Modeling in Psychopathology: The Importance of Contemporaneous and Temporal Connections.Getting the most out of intensive longitudinal data: a methodological review of workload-injury studies
P2860
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
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name
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
@ast
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
@en
type
label
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
@ast
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
@en
prefLabel
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
@ast
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
@en
P2860
P356
P1476
What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.
@en
P2093
Ellen L Hamaker
Silvia de Haan-Rietdijk
P2860
P356
10.3389/FPSYG.2016.00891
P407
P577
2016-06-14T00:00:00Z