effectsize: Estimation of Effect Size Indices and Standardized Parameters

Ben‐Shachar, Mattan S.; Lüdecke, Daniel; Makowski, Dominique

doi:10.21105/joss.02815

Cited by 1,155 publications

(690 citation statements)

References 11 publications

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“…All statistical analyses were conducted using the R programming language (version Alpha levels for all analyses were set to 0.05. Where relevant, partial eta-squared (ηp 2 ) was estimated using the 'effectsize' package 71 . Bayes factors were estimated using the 'BayesFactor' package 72 .…”

Section: Discussionmentioning

confidence: 99%

Region-specific elevations of glutamate + glutamine correlate with the sensory symptoms of autism spectrum disorders

He¹,

Oeltzschner²,

Mikkelsen³

et al. 2021

Preprint

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Individuals on the autism spectrum are often reported as being hyper- and/or hypo-reactive to sensory input. These sensory disturbances were one of the key observations that led to the development of the altered excitation-inhibition (E-I) model of autism, which posits that an increase ratio of excitatory to inhibitory signaling may explain certain phenotypical expressions of autism spectrum disorders (ASD). While there has been strong support for the altered E-I model of autism, much of the evidence has come from animal models. With regard to in-vivo human studies, evidence for altered E-I balance in ASD come from studies adopting magnetic resonance spectroscopy (MRS). Spectral-edited MRS can be used to provide measures of the levels of GABA+ (GABA + macromolecules) and Glx (glutamate + glutamine) in specific brain regions as proxy markers of excitation and inhibition respectively. In the current study, we found region-specific elevations of Glx elevated in the sensorimotor cortex but not thalamus) but not GABA+ in ASD. Higher levels of Glx were associated with more parent reported difficulties of hyper- and hypo-reactivity to sensory input, as well as reduced feed-forward inhibition during tactile perception in children with ASD. Together, these results provide strong empirical support for increased excitation by way of elevated Glx in ASD. Critically, our results also provide a clear link between Glx and the sensory symptoms of ASD at both behavioral and perceptual levels.

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Section: Discussionmentioning

confidence: 99%

Region-specific elevations of glutamate + glutamine correlate with the sensory symptoms of autism spectrum disorders

He¹,

Oeltzschner²,

Mikkelsen³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Similarly, line plots of sex and hemisphere effects were produced by predicting the mean values for each sex and hemisphere at mean age and eTIV. For evaluating the interrelations between the age, sex, or hemisphere-related variations in the regional WM volumes and DWI properties, we first computed the standardised parameter estimates (β*) for the respective terms in each metric using the robust standardization through refitting, implemented with the effectsize package (Ben-Shachar et al, 2020). Then, the β* values across 27 (or 21, in the case of hemisphere effects) ROIs were used to compute Pearson's correlation between the pairwise metrics.…”

Section: Discussionmentioning

confidence: 99%

Changes in regional white matter volumetry and microstructure during the post-adolescence period: a cross-sectional study of a cohort of 1,713 university students

Tsuchida

Laurent

Crivello

et al. 2021

Preprint

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Human brain white matter undergoes a protracted maturation that continues well into adulthood. Recent advances in diffusion-weighted imaging (DWI) methods allow detailed characterizations of the microstructural architecture of white matter, and they are increasingly utilised to study white matter changes during development and ageing. However, relatively little is known about the late maturational changes in the microstructural architecture of white matter during post-adolescence. Here we report on regional changes in white matter volume and microstructure in young adults undergoing university-level education. As part of the MRi-Share multi-modal brain MRI database, multi-shell, high angular resolution DWI data were acquired in a unique sample of 1,713 university students aged 18 to 26. We assessed the age and sex dependence, as well as hemispheric asymmetry of diffusion metrics derived from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), in the white matter regions as defined in the John Hopkins University (JHU) white matter labels atlas. We demonstrate that while regional white matter volume is relatively stable over the age range of our sample, the white matter microstructural properties show clear age-related variations. Globally, it is characterised by a robust increase in neurite density index (NDI), and to a lesser extent, orientation dispersion index (ODI). These changes are accompanied by a decrease in diffusivity. In contrast, there is minimal age-related variation in fractional anisotropy. There are regional variations in these microstructural changes: some tracts, most notably cingulum bundles, show a strong age-related increase in NDI coupled with decreases in radial and mean diffusivity, while others, mainly cortico-spinal projection tracts, primarily show an ODI increase and axial diffusivity decrease. These age-related variations are not different between males and females, but males show higher NDI and ODI and lower diffusivity than females across many tracts. We also report a robust hemispheric asymmetry in both the volume and microstructural properties in many regions. These findings emphasise the complexity of changes in white matter structure occurring in this critical period of late maturation in early adulthood.

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“…Internally, data cleaning is carried out using the tidyverse (Wickham et al, 2019), while statistical analysis is carried out via the statsExpressions and easysta ts (Ben-Shachar et al, 2020;Lüdecke et al, 2019Lüdecke et al, , 2020Lüdecke et al, , 2021Makowski et al, 2019Makowski et al, , 2020 packages. All visualizations are constructed using the grammar of graphics framework (Wilkinson, 2012), as implemented in the ggplot2 package (Wickham, 2016).…”

Section: Statement Of Needmentioning

confidence: 99%