2015
DOI: 10.3389/fpsyg.2015.01438
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Using item response theory to investigate the structure of anticipated affect: do self-reports about future affective reactions conform to typical or maximal models?

Abstract: In the present research, we used item response theory (IRT) to examine whether effective predictions (anticipated affect) conforms to a typical (i.e., what people usually do) or a maximal behavior process (i.e., what people can do). The former, correspond to non-monotonic ideal point IRT models, whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N = 1624) was used. Participants were asked to report on anticipated positive and negative affect around a… Show more

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Cited by 8 publications
(7 citation statements)
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“…Overall, they found a very high level of mixed emotions across their profiles. Complementary to the evidence reviewed above focusing on current affect and emotions, their findings bring convincing support for the co-occurrence of anticipated emotions as well (see also, Zampetakis et al, 2015Zampetakis et al, , 2016b.…”
Section: % 3 0 4 !supporting
confidence: 56%
“…Overall, they found a very high level of mixed emotions across their profiles. Complementary to the evidence reviewed above focusing on current affect and emotions, their findings bring convincing support for the co-occurrence of anticipated emotions as well (see also, Zampetakis et al, 2015Zampetakis et al, , 2016b.…”
Section: % 3 0 4 !supporting
confidence: 56%
“…However, the amount of variance explained by the first component was 34.1% for the Mathematics data (an eigenvalue of 12.26) and 35.9% for the German data (an eigenvalue of 12.93), suggesting reasonable support for the suitability of the data for the application of the GGUM (cf. Zampetakis et al, 2015).…”
Section: Resultsmentioning
confidence: 99%
“…In practice, however, this assumption does not strictly hold. Therefore, it is considered reasonable if there is a dominant factor in the data; in other words, item response models (IRM) will perform well as long as the latent factor being measured dominates the others (Zampetakis et al 2015). This assumption was tested using the polychoric correlation matrix and principal component analysis (PCA) for all items together and for the subsets of items by domain.…”
Section: Methodsmentioning
confidence: 99%