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Authors = Clemens Draxler

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12 pages, 1479 KiB  
Article
Mental Paper Folding Revisited: The Involvement of Visual Action Imagery
by Stephan Frederic Dahm and Clemens Draxler
Psych 2023, 5(1), 14-25; https://doi.org/10.3390/psych5010002 - 30 Dec 2022
Cited by 2 | Viewed by 3583
Abstract
Action imagery describes a mental representation of an action and its consequences. Although it is widely recognized that people differ in their ability to imagine actions, objective validated tests to measure such differences are scarce. In search of an objective testing method for [...] Read more.
Action imagery describes a mental representation of an action and its consequences. Although it is widely recognized that people differ in their ability to imagine actions, objective validated tests to measure such differences are scarce. In search of an objective testing method for action imagery ability, the present study investigated whether solving mental paper-folding tasks involves action imagery. The stimuli were two-dimensional grids of six squares. A total of 99 participants mentally folded each grid into a three-dimensional cube to judge whether two highlighted lines in the grid overlapped in the imagined cube. This was done in two sessions of 214 judgements each, where the grids differed in overlaps, the least number of imagined folds, and the least number of imagined directional changes. Error rates and reaction times increased with the number of imagined folds and with the number of directional changes. Furthermore, more errors were committed with overlapping lines than with no overlaps. This was not reflected in the reaction times. Hence, the reaction times increased when the stepwise folding process was enlarged, but not when the final selection was more difficult. We concluded that the participants predominantly used action imagery as a task-solving strategy rather than for abstract problem-solving. Full article
(This article belongs to the Special Issue Prominent Papers in Psych  2021–2023!)
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13 pages, 360 KiB  
Article
Conditional Inference in Small Sample Scenarios Using a Resampling Approach
by Clemens Draxler and Andreas Kurz
Stats 2021, 4(4), 837-849; https://doi.org/10.3390/stats4040049 - 15 Oct 2021
Cited by 2 | Viewed by 2607
Abstract
This paper discusses a non-parametric resampling technique in the context of multidimensional or multiparameter hypothesis testing of assumptions of the Rasch model. It is based on conditional distributions and it is suggested in small sample size scenarios as an alternative to the application [...] Read more.
This paper discusses a non-parametric resampling technique in the context of multidimensional or multiparameter hypothesis testing of assumptions of the Rasch model. It is based on conditional distributions and it is suggested in small sample size scenarios as an alternative to the application of asymptotic or large sample theory. The exact sampling distribution of various well-known chi-square test statistics like Wald, likelihood ratio, score, and gradient tests as well as others can be arbitrarily well approximated in this way. A procedure to compute the power function of the tests is also presented. A number of examples of scenarios are discussed in which the power function of the test does not converge to 1 with an increasing deviation of the true values of the parameters of interest from the values specified in the hypothesis to be tested. Finally, an attempt to modify the critical region of the tests is made aiming at improving the power and an R package is provided. Full article
(This article belongs to the Special Issue Re-sampling Methods for Statistical Inference of the 2020s)
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11 pages, 832 KiB  
Article
Conditional or Pseudo Exact Tests with an Application in the Context of Modeling Response Times
by Clemens Draxler and Stephan Dahm
Psych 2020, 2(4), 198-208; https://doi.org/10.3390/psych2040017 - 30 Oct 2020
Cited by 6 | Viewed by 2550
Abstract
This paper treats a so called pseudo exact or conditional approach of testing assumptions of a psychometric model known as the Rasch model. Draxler and Zessin derived the power function of such tests. They provide an alternative to asymptotic or large sample theory, [...] Read more.
This paper treats a so called pseudo exact or conditional approach of testing assumptions of a psychometric model known as the Rasch model. Draxler and Zessin derived the power function of such tests. They provide an alternative to asymptotic or large sample theory, i.e., chi square tests, since they are also valid in small sample scenarios. This paper suggests an extension and applies it in a research context of investigating the effects of response times. In particular, the interest lies in the examination of the influence of response times on the unidimensionality assumption of the model. A real data example is provided which illustrates its application, including a power analysis of the test, and points to possible drawbacks. Full article
(This article belongs to the Special Issue Learning from Psychometric Data)
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