ArticleScientific reports2021
A comparison of continuous and discrete time modeling of affective processes in terms of predictive accuracy.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Designing Learning Intervention Studies: Identifiability of Heterogeneous Hidden Markov Models.Psychometrika · 2025Article
- Chasing consistency: On the measurement error in self-reported affect in experiments.Behavior research methods · 2024Article
- Behavior Data Analysis of English Learners Based on Discrete Dynamic System Modeling Method.Computational intelligence and neuroscience · 2022Article
- A Tutorial on Analyzing Ecological Momentary Assessment Data in Psychological Research With Bayesian (Generalized) Mixed-Effects Models.Advances in methods and practices in psychological scienceArticle
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Authors and funding
3 authors.
Funding
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Abstract
Intra-individual processes are thought to continuously unfold across time. For equally spaced time intervals, the discrete-time lag-1 vector autoregressive (VAR(1)) model and the continuous-time Ornstein-Uhlenbeck (OU) model are equivalent. It is expected that by taking into account the unequal spacings of the time intervals in real data between observations will lead to an advantage for the OU in terms of predictive accuracy. In this paper, this is claim is being investigated by comparing the predictive accuracy of the OU model to that of the VAR(1) model on typical ESM data obtained in the context of affect research. It is shown that the VAR(1) model outperforms the OU model for the majority of the time series, even though time intervals in the data are unequally spaced. Accounting for measurement error does not change the result. Deleting large abrupt changes on short time intervals (that may be caused by externally driven events) does however lead to a significant improvement for the OU model. This suggests that processes in psychology may be continuously evolving, but that there are factors, like external events, which can disrupt the continuous flow.
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Registered trials
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