Refine
Year of publication
Document Type
- Article (211)
- Postprint (85)
- Conference Proceeding (7)
- Monograph/Edited Volume (3)
- Preprint (2)
- Review (2)
- Doctoral Thesis (1)
- Part of Periodical (1)
Keywords
- reading (15)
- eye movements (14)
- Eye movements (12)
- Reading (10)
- Chinese (9)
- preview benefit (7)
- perceptual span (6)
- individual differences (5)
- Eye movement (4)
- Linear mixed model (4)
Institute
- Department Psychologie (267)
- Extern (17)
- Department Linguistik (16)
- Strukturbereich Kognitionswissenschaften (14)
- Department Sport- und Gesundheitswissenschaften (8)
- Institut für Physik und Astronomie (7)
- Humanwissenschaftliche Fakultät (3)
- Fakultät für Gesundheitswissenschaften (2)
- Lehreinheit für Wirtschafts-Arbeit-Technik (2)
- Institut für Chemie (1)
Untitled - Introduction
(2001)
Sequential and coordinative processing dynamics in figural transformations across the life span
(1996)
The authors demonstrate that the timing and sequencing of target durations require low-level timing and executive control. Sixteen young (M-age = 19 years) and 16 older (M-age = 70 years) adults participated in 2 experiments. In Experiment 1, individual mean-variance functions for low-level timing (isochronous tapping) and the sequencing of multiple targets (rhythm production) revealed (a) a dissociation of low-level timing and sequencing in both age groups, (b) negligible age differences for low-level timing, and (c) large age differences for sequencing. Experiment 2 supported the distinction between low-level timing and executive functions: Selection against a dominant rhythm and switching between rhythms impaired performances in both age groups and induced pronounced perseveration of the dominant pattern in older adults.
Sequential and coordinative complexity : age-based processing limitations in figural transformations
(1993)
Dimensions of cognitive complexity in figural transformations were examined in the context of adult age differences. Sequential complexity was manipulated through figural transformations of single objects in a multiple-object array. Coordinative complexity was induced through spatial or nonspatial transformations of the entire array. Results confirmed the prediction that age-related slowing is larger in coordinative complexity than in sequential complexity conditions. The effect was stable across 8 sessions (Experiment 1), was obtained when age groups were equated in accuracy with criterion-referenced testing (Experiment 2), and was corroborated by age-differential probabilities of error types (Experiments 1 and 2). A model is proposed attributing age effects under coordinative complexity to 2 factors: (a) basic-level slowing and (b) time-consuming reiterations through the processing sequence due to age-related working memory failures.
Sequential and coordinative complexity : age-based processing limitations in figural transformation
(1993)
Dimensions of cognitive complexity in figural transformations were examined in the context of adult age differences. Sequential complexity was manipulated through figural transformations of single objects in a multiple- object array. Coordinative complexity was induced through spatial or nonspatial transformations of the entire array. Results confirmed the prediction that age-related slowing is larger in coordinative complexity than in sequential complexity conditions. The effect was stable across 8 sessions (Exp 1), was obtained when age groups were equated in accuracy with criterion-referenced testing (Exp 2), and was corroborated by age-differential probabilities of error types (Exps 1 and 2). A model is proposed attributing age effects under coordinative complexity to 2 factors: (1) basic- level slowing and (2) time-consuming reiterations through the processing sequence due to age-related working memory failures. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Linear mixed-effects models have increasingly replaced mixed-model analyses of variance for statistical inference in factorial psycholinguistic experiments. Although LMMs have many advantages over ANOVA, like ANOVAs, setting them up for data analysis also requires some care. One simple option, when numerically possible, is to fit the full variance covariance structure of random effects (the maximal model; Barr, Levy, Scheepers & Tily, 2013), presumably to keep Type I error down to the nominal a in the presence of random effects. Although it is true that fitting a model with only random intercepts may lead to higher Type I error, fitting a maximal model also has a cost: it can lead to a significant loss of power. We demonstrate this with simulations and suggest that for typical psychological and psycholinguistic data, higher power is achieved without inflating Type I error rate if a model selection criterion is used to select a random effect structure that is supported by the data. (C) 2017 The Authors. Published by Elsevier Inc.
The Smoothing Spline ANOVA (SS-ANOVA) requires a specialized construction of basis and penalty terms in order to incorporate prior knowledge about the data to be fitted. Typically, one resorts to the most general approach using tensor product splines. This implies severe constraints on the correlation structure, i.e. the assumption of isotropy of smoothness can not be incorporated in general. This may increase the variance of the spline fit, especially if only a relatively small set of observations are given. In this article, we propose an alternative method that allows to incorporate prior knowledge without the need to construct specialized bases and penalties, allowing the researcher to choose the spline basis and penalty according to the prior knowledge of the observations rather than choosing them according to the analysis to be done. The two approaches are compared with an artificial example and with analyses of fixation durations during reading.
The Smoothing Spline ANOVA (SS-ANOVA) requires a specialized construction of basis and penalty terms in order to incorporate prior knowledge about the data to be fitted. Typically, one resorts to the most general approach using tensor product splines. This implies severe constraints on the correlation structure, i.e. the assumption of isotropy of smoothness can not be incorporated in general. This may increase the variance of the spline fit, especially if only a relatively small set of observations are given. In this article, we propose an alternative method that allows to incorporate prior knowledge without the need to construct specialized bases and penalties, allowing the researcher to choose the spline basis and penalty according to the prior knowledge of the observations rather than choosing them according to the analysis to be done. The two approaches are compared with an artificial example and with analyses of fixation durations during reading.