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Analysing state dependences in emotional experiences by dynamic count data models

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  • Ulf Böckenholt

Abstract

Summary. 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.

Suggested Citation

  • Ulf Böckenholt, 2003. "Analysing state dependences in emotional experiences by dynamic count data models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(2), pages 213-226, May.
    • Handle: RePEc:bla:jorssc:v:52:y:2003:i:2:p:213-226
    DOI: 10.1111/1467-9876.00399
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    1. Lindsey, J. K., 1999. "Models for Repeated Measurements," OUP Catalogue, Oxford University Press, edition 2, number 9780198505594.
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    Cited by:

    1. Feike C. Drost & Ramon Van Den Akker & Bas J. M. Werker, 2008. "Local asymptotic normality and efficient estimation for INAR(p) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 783-801, September.
    2. Francesco Bravo, 2011. "Comment on: Subsampling weakly dependent time series and application to extremes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 483-486, November.
    3. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2008. "Efficient Estimation of Autoregression Parameters and Innovation Distributions forSemiparametric Integer-Valued AR(p) Models (Revision of DP 2007-23)," Other publications TiSEM cef533d0-6b49-4ce9-8cd2-7, Tilburg University, School of Economics and Management.

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