Conference Object

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
  • Author(s) / Creator(s)
    Mews, Sina
  • PsychArchives acquisition timestamp
    2021-05-14T12:11:26Z
  • Made available on
    2021-05-14T12:11:26Z
  • Date of first publication
    2021-05-19
  • 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.
    en
  • Publication status
    unknown
    en
  • Review status
    unknown
    en
  • 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
    en
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/4263
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.4826
  • Language of content
    eng
  • Publisher
    ZPID (Leibniz Institute for Psychology)
    en
  • Is part of
    Research Synthesis & Big Data, 2021, online
    en
  • Dewey Decimal Classification number(s)
    150
  • Title
    Continuous-time state-space modelling of delinquent behaviour in adolescence and young adulthood
    en
  • DRO type
    conferenceObject
    en
  • Visible tag(s)
    ZPID Conferences and Workshops