Examining interindividual differences in cyclicity of pleasant and unpleasant affects using spectral analysis and item response modeling

Nilam Ram, S. Y.Miin Chow, Ryan P. Bowles, Lijuan Wang, Kevin Grimm, Frank Fujita, John R. Nesselroade

Research output: Contribution to journalArticle

30 Scopus citations

Abstract

Weekly cycles in emotion were examined by combining item response modeling and spectral analysis approaches in an analysis of 179 college students' reports of daily emotions experienced over 7 weeks. We addressed the measurement of emotion using an item response model. Spectral analysis and multilevel sinusoidal models were used to identify interindividual differences in intraindividual cyclic change. Simulations and incomplete data designs were used to examine how well this combination of analysis techniques might work when applied to other practical data problems. Empirically, we found systematic individual differences in the extent to which individuals' emotions follow a weekly cycle, and in how such cycles are exhibited. Weekly cycles accounted for very little variance in day to day emotions at the individual level. Analytically, we illustrate how measurement, change, and interindividual difference models from different traditions may be combined in a practical manner to describe some of the complexities of human behavior.

Original languageEnglish (US)
Pages (from-to)773-790
Number of pages18
JournalPsychometrika
Volume70
Issue number4
DOIs
StatePublished - Dec 1 2005
Externally publishedYes

Keywords

  • Emotion
  • Longitudinal
  • Missing data
  • Multilevel
  • Non-linear

ASJC Scopus subject areas

  • Psychology(all)
  • Applied Mathematics

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