Continuous-time state-space modelling of delinquent behaviour in adolescence and young adulthood
Author(s) / Creator(s)
Mews, Sina
Abstract / Description
Using data from a longitudinal study on delinquent behaviour of adolescents in Germany, we investigate the persistence of an individual’s delinquency level over time. We assume the latter to be a latent trait underlying the observed trajectories of adolescents' delinquency, thus using a state-space model (SSM) to analyse the data. As the observations are irregularly spaced in time, we formulate the SSM in continuous time and specify the state process as an Ornstein-Uhlenbeck process. We further include the adolescents’ gender and age as covariates in the observation process. Statistical inference is carried out by maximum approximate likelihood estimation, where multiple numerical integration within the likelihood evaluation is performed via a fine discretisation of the state process. The corresponding reframing of the SSM as a continuous-time hidden Markov model enables us to apply the associated efficient algorithms for parameter estimation and state decoding. The results reveal temporal persistence in the deviation of an individual's delinquency level from the population mean.
Persistent Identifier
Date of first publication
2021-05-19
Is part of
Research Synthesis & Big Data, 2021, online
Publisher
ZPID (Leibniz Institute for Psychology)
Citation
Mews, S. (2021). Continuous-time state-space modelling of delinquent behaviour in adolescence and young adulthood. ZPID (Leibniz Institute for Psychology). https://doi.org/10.23668/PSYCHARCHIVES.4826
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Author(s) / Creator(s)Mews, Sina
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PsychArchives acquisition timestamp2021-05-14T12:11:26Z
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Made available on2021-05-14T12:11:26Z
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Date of first publication2021-05-19
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Abstract / DescriptionUsing data from a longitudinal study on delinquent behaviour of adolescents in Germany, we investigate the persistence of an individual’s delinquency level over time. We assume the latter to be a latent trait underlying the observed trajectories of adolescents' delinquency, thus using a state-space model (SSM) to analyse the data. As the observations are irregularly spaced in time, we formulate the SSM in continuous time and specify the state process as an Ornstein-Uhlenbeck process. We further include the adolescents’ gender and age as covariates in the observation process. Statistical inference is carried out by maximum approximate likelihood estimation, where multiple numerical integration within the likelihood evaluation is performed via a fine discretisation of the state process. The corresponding reframing of the SSM as a continuous-time hidden Markov model enables us to apply the associated efficient algorithms for parameter estimation and state decoding. The results reveal temporal persistence in the deviation of an individual's delinquency level from the population mean.en
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Publication statusunknownen
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Review statusunknownen
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CitationMews, S. (2021). Continuous-time state-space modelling of delinquent behaviour in adolescence and young adulthood. ZPID (Leibniz Institute for Psychology). https://doi.org/10.23668/PSYCHARCHIVES.4826en
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/4263
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.4826
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Language of contenteng
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PublisherZPID (Leibniz Institute for Psychology)en
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Is part ofResearch Synthesis & Big Data, 2021, onlineen
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Dewey Decimal Classification number(s)150
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TitleContinuous-time state-space modelling of delinquent behaviour in adolescence and young adulthooden
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DRO typeconferenceObjecten
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Visible tag(s)ZPID Conferences and Workshops