Analysing state dependences in emotional experiences by dynamic count data models

Ulf Böckenholt*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The paper presents a multilevel framework for the analysis of multivariate count data that are observed over several time periods for a random sample of individuals. The approach proposed facilitates studying observed and unobserved sources of dependences among the event categories in the presence of possibly higher order autoregressive effects. In an investigation of the relationships between pleasant and unpleasant emotional experiences and the personality traits neuroticism and extraversion over time, we find that the two personality factors are related to both the mean rates of the emotional experiences and their carry-over effects. Respondents with high neuroticism scores not only reported more unpleasant than pleasant emotional experiences but also exhibited higher carry-over effects for unpleasant than for pleasant emotions. In contrast, respondents with high extraversion scores reported fewer anxiety and more euphoria emotions than respondents with low extraversion scores with weaker carry-over effects for both pleasant and unpleasant emotions.

Original languageEnglish (US)
Pages (from-to)213-226
Number of pages14
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume52
Issue number2
DOIs
StatePublished - Oct 1 2003

Keywords

  • Autoregression
  • Binomial thinning
  • Count data
  • Multilevel models
  • Overdispersion

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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