Accounting for Variable Task Discrimination in Divergent Thinking Fluency Measurement: An Example of the Benefits of a 2‐Parameter Poisson Counts Model and its Bifactor Extension Over the Rasch Poisson Counts Model

A Flexible Approach to Modeling Over-, Under- and Equidispersed Count Data in IRT: The Two-Parameter Conway-Maxwell-Poisson Model

10.31234/osf.io/c8efg ◽

2021 ◽

Author(s):

Marie Beisemann

Keyword(s):

Count Data ◽

Divergent Thinking ◽

Poisson Model ◽

Likelihood Method ◽

Marginal Maximum Likelihood ◽

Irt Model ◽

Special Cases ◽

The One ◽

Two Parameter ◽

Poisson Counts

Several psychometric tests generate count data, e.g. the number of ideas in divergent thinkingtasks. The most prominent count data IRT model, the Rasch Poisson Counts Model (RPCM)assumes constant discriminations across items as well as the equidispersion assumption of thePoisson distribution (i.e., E(X) = Var(X)), considerably limiting modeling flexibility. Violationsof these assumptions are associated with impaired ability, reliability, and standard error estimates.Models have been proposed to loose the one or the other assumption. The Two-Parameter PoissonCounts Model (2PPCM) allows varying discriminations but retains the equidispersion assumption.The Conway-Maxwell-Poisson Counts Model (CMPCM) that allows for modeling equi- but alsoover- and underdispersion (more or less variance than implied by the mean under the Poisson distribution)but assumes constant discriminations. The present work introduces the Two-ParameterConway-Maxwell-Poisson (2PCMP) model which generalizes the RPCM, the 2PPCM, and the CMPCM(all contained as special cases) to allow for varying discriminations and dispersions withinone model. A marginal maximum likelihood method based on a fixed quadrature Expectation-Maximization (EM) algorithm is derived. Standard errors as well as two methods for latent abilityestimation are provided. An implementation of the 2PCMP model in R and C++ is provided. Twosimulation studies examine the model’s statistical properties and compare the 2PCMP model toestablished methods. Data from divergent thinking tasks are re-analyzed with the 2PCMP modelto illustrate the model’s flexibility and ability to test assumptions of special cases.

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Variations Across the Menstrual Cycle in EEG Activity During Thinking and Mental Relaxation

Journal of Psychophysiology ◽

10.1027//0269-8803.13.3.163 ◽

1999 ◽

Vol 13 (3) ◽

pp. 163-172 ◽

Cited By ~ 7

Author(s):

R. Krug ◽

M. Mölle ◽

H.L. Fehm ◽

J. Born

Keyword(s):

Menstrual Cycle ◽

Divergent Thinking ◽

Spectral Power ◽

Plasma Concentrations ◽

Task Demands ◽

Menstrual Phase ◽

Convergent Thinking ◽

Eeg Activity ◽

Dimensional Complexity ◽

Mental Relaxation

Abstract Previous studies have indicated: (1) peak performance on tests of divergent creative thinking during the ovulatory phase of the menstrual cycle; (2) compared to convergent analytical thinking, divergent thinking was found to be associated with a distinctly increased dimensional complexity of ongoing EEG activity. Based on these findings, we hypothesized that cortical information processing during the ovulatory phase is characterized by an increased EEG dimensionality. Each of 16 women was tested on 3 occasions: during the ovulatory phase, the luteal phase, and menses. Presence of the phases was confirmed by determination of plasma concentrations of estradiol, progesterone, and luteinizing hormone. The EEG was recorded while the women performed: (1) tasks of divergent thinking; (2) tasks of convergent thinking; and (3) during mental relaxation. In addition to EEG dimensional complexity, conventional spectral power analysis was performed. Behavioral data confirmed enhanced creative performance during the ovulatory phase while convergent thinking did not vary across cycle phases. EEG complexity was higher during divergent than convergent thought, but this difference remained unaffected by the menstrual phase. Influences of the menstrual phase on EEG activity were most obvious during mental relaxation. In this condition, women during the ovulatory phase displayed highest EEG dimensionality as compared with the other cycle phases, with this effect being most prominent over the central and parietal cortex. Concurrently, power within the alpha frequency band as well as theta power at frontal and parietal leads were lower during the luteal than ovulatory phase. EEG results indicate that task demands of thinking overrode effects of menstrual cycle. However, with a less demanding situation, an ovulatory increase in EEG dimensionality became prominent suggesting a loosening of associative habits during this phase.

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Measurement Invariance of Divergent Thinking Across Gender, Age, and School Forms

European Journal of Psychological Assessment ◽

10.1027/1015-5759.25.1.1 ◽

2009 ◽

Vol 25 (1) ◽

pp. 1-7 ◽

Cited By ~ 12

Author(s):

Jörg-Tobias Kuhn ◽

Heinz Holling

Keyword(s):

Measurement Invariance ◽

Divergent Thinking ◽

Factor Model ◽

Age Groups ◽

Thinking Skills ◽

Specific Model ◽

Confirmatory Factor Analyses ◽

Domain Specific ◽

Gender And Age ◽

Confirmatory Factor

The present study explores the factorial structure and the degree of measurement invariance of 12 divergent thinking tests. In a large sample of German students (N = 1328), a three-factor model representing verbal, figural, and numerical divergent thinking was supported. Multigroup confirmatory factor analyses revealed that partial strong measurement invariance was tenable across gender and age groups as well as school forms. Latent mean comparisons resulted in significantly higher divergent thinking skills for females and students in schools with higher mean IQ. Older students exhibited higher latent means on the verbal and figural factor, but not on the numerical factor. These results suggest that a domain-specific model of divergent thinking may be assumed, although further research is needed to elucidate the sources that negatively affect measurement invariance.

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Dreamlike and Playful Virtual Environments to Inspire Children’s Divergent Thinking

Journal of Media Psychology Theories Methods and Applications ◽

10.1027/1864-1105/a000279 ◽

2020 ◽

pp. 1-11

Author(s):

Jérôme Guegan ◽

Claire Brechet ◽

Julien Nelson

Keyword(s):

Virtual Environments ◽

Divergent Thinking ◽

Idea Generation ◽

Combined Processes ◽

Office Environment ◽

School Aged Children

Abstract. Computers have long been seen as possible tools to foster creativity in children. In this respect, virtual environments present an interesting potential to support idea generation but also to steer it in relevant directions. A total of 96 school-aged children completed a standard divergent thinking task while being exposed to one of three virtual environments: a replica of the headmistress’s office, a replica of their schoolyard, and a dreamlike environment. Results showed that participants produced more original ideas in the dreamlike and playful environments than in the headmistress’s office environment. Additionally, the contents of the environment influenced the selective exploration of idea categories. We discuss these results in terms of two combined processes: explicit references to sources of inspiration in the environment, and the implicit priming of specific idea categories.

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