Affect Pattern Recognition: Using Discrete Hidden Markov Models for Discriminate Distressed from Nondistressed Couples.

Self-report affect sequences generated during a conversation between spouses were used to illustrate how Hidden Markov Model (HMM) methodology can classify couples according to marital quality. This pattern recognition technique allows an investigator to characterize processes that generate observab...

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Publicado en:Marriage & Family Review Vol. 34; no. 1/2; pp. 139 - 165
Autor principal: Griffin, William A.
Formato: Artículo
Publicado: Taylor & Francis Ltd 2002
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Affect Pattern Recognition: Using Discrete Hidden Markov Models for Discriminate Distressed from Nondistressed Couples.
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        au: Griffin, William A.
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        Affect (Psychology)
        Pattern perception
        Marriage
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        subj:
          Affect (Psychology)
          Pattern perception
          Marriage
      ab: Self-report affect sequences generated during a conversation between spouses were used to illustrate how Hidden Markov Model (HMM) methodology can classify couples according to marital quality. This pattern recognition technique allows an investigator to characterize processes that generate observable phenomena—in these data, expressed affect. I introduce the conceptual foundations and, briefly, the methodology of HMM and discuss its potential use in social and behavioral research. To illustrate the potential value of this method, I show how sequences of self-reported affect, derived in real-time during a laboratory interaction between 30 married partners, can successfully discriminate between distressed and nondistressed marital relationships.
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      src: R
    language: English
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