Summary Plots With Adjusted Error Bars: The <i>superb</i> Framework With an Implementation in R

Cousineau, Denis; Goulet, Marc-André; Harding, Bradley

doi:10.1177/25152459211035109

Cited by 32 publications

(28 citation statements)

References 51 publications

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“…(b) Presence of the color singleton distractor speeded responses and improved accuracy, indicating suppression. Error bars in all figures represent within-subject standard errors (Cousineau et al, 2021). See the online article for the color version of this figure.…”

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confidence: 99%

Ignoring the unknown: Attentional suppression of unpredictable visual distraction.

Ma¹,

Abrams²

2023

Journal of Experimental Psychology: Human Perception and Perfor

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Recent findings have shown that people are capable of proactively inhibiting salient visual distractors in a scene when they know the color of the distractor, enhancing efficient search. Investigations of this suppression effect have concluded that it is not possible to suppress a distractor of an unknown color, implying a mechanism that operates only on a first-order, feature-specific level. However, with a modification to the search task, we show here for the first time that people can indeed suppress salient uniquely colored distractors even when not knowing their color in advance. The task requires participants to search for the most prevalent of several shapes in the display. In two experiments the presence of an unpredictable-color singleton facilitated search. An experiment with briefly presented probes confirmed proactive prevention of capture by the distractor. The results reveal a second-order or global-salience-based suppressive mechanism that facilitates visual processing. Public Significance StatementNatural visual scenes contain more information than can be processed at once, so the visual system must select portions of a scene for further processing. One way in which that selection occurs is by suppressing elements known to be irrelevant to one's current goals. Previous research has suggested that this suppression is possible only if specific features of the unwanted elements (e.g., their color) are known in advance; however, we show here, with a simple change to the experimental task, that people are indeed capable of suppressing distractors even without advance knowledge of their specific features. The results reveal a new mechanism that enhances efficient visual selection from the environment.

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confidence: 99%

Ignoring the unknown: Attentional suppression of unpredictable visual distraction.

Ma¹,

Abrams²

2023

Journal of Experimental Psychology: Human Perception and Perfor

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“…When visually inspecting the outputs generated with the syntax collection, it needs to be kept in mind that the CIs plotted around arithmetic means are unadjusted stand-alone CIs ( Cousineau et al, 2021 ). These intervals are of limited use for the comparison between groups and particularly problematic with regard to comparing between factor levels in within-subject designs ( Loftus and Masson, 1994 ).…”

Section: Discussionmentioning

confidence: 99%

“…These intervals are of limited use for the comparison between groups and particularly problematic with regard to comparing between factor levels in within-subject designs ( Loftus and Masson, 1994 ). Users interested in visualizing adjusted CIs are recommended to consider the R -based library superb ( Cousineau et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

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Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial

Loffing

2022

Front. Psychol.

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Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

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“…The scores of the D2-R and psychological variables are reported as means with within-subject correlation-adjusted error bars ( M ± CI), with CI representing the 95% CI normalized to account for the within-subjects design ( Cousineau, 2005 ; Cousineau et al, 2021 ). We computed pre-post intervention change scores for all cognitive and psychological measures

which are reported as means with SD ( M ± SD ).…”

Section: Methodsmentioning

confidence: 99%

Online Mindfulness Intervention, Mental Health and Attentional Abilities: A Randomized Controlled Trial in University Students During COVID-19 Lockdown

2022

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The COVID-19 pandemic has led to worldwide restrictive measures, raising concerns about mental health in young adults who were not particularly vulnerable to the virus itself. This study investigated the impact of these restrictions on mental and cognitive health of university students, and tested the efficacy of a brief online mindfulness meditation intervention in countering psychological distress and improving attentional abilities. Ninety-six university students forced into remote learning due to COVID-19 pandemic restrictions and with no experience in meditation were randomly assigned to either a passive control group (n = 48) or to an experimental group (n = 48) following daily, for 17 days, an online mindfulness intervention (10–20 min per day). Due to drop-out, 38 participants in each group were finally analyzed. Pre- and post-tests assessed participants’ mental health (psychological well-being, depression, anxiety, stress) and attentional abilities. The analysis of baseline data in comparison with normative scores and pre-pandemic statistics confirmed the expected psychological distress, but it did not reveal any attentional deficits in our participants. Pre-post change scores analyses showed a reduction in stress (p = 0.006, ηp2 = 0.10), anxiety (p = 0.002, ηp2 = 0.13), and depression (p = 0.025, ηp2 = 0.07), and an improvement in well-being (p = 0.013, ηp2 = 0.12) in the experimental group, but not in the control group. In both groups, no significant effect was found on attentional abilities. Our results confirmed the psychological vulnerability of higher education students in the midst of the remote learning period during the second COVID-19 lockdown in France, while suggesting preservation of attentional functioning. Although the tested mindfulness intervention did not enhance the attentional abilities in already good performing students, it did promote their mental health. This study offers additional evidence on the feasibility and efficacy of mindfulness-based interventions in students during psychologically straining periods, like the COVID-19 pandemic.

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Summary Plots With Adjusted Error Bars: The superb Framework With an Implementation in R

Cited by 32 publications

References 51 publications

Ignoring the unknown: Attentional suppression of unpredictable visual distraction.

Ignoring the unknown: Attentional suppression of unpredictable visual distraction.

Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial

Online Mindfulness Intervention, Mental Health and Attentional Abilities: A Randomized Controlled Trial in University Students During COVID-19 Lockdown

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