22 papers · ranked by Valyu relevance
Juyoung Jung, Ariel M. Aloe
Meta-analyses often use standardized mean differences (SMDs), such as Cohen's d and Hedges' g, to compare treatment effects. However, these SMDs are highly sensitive to the within-study sample variability used for their standardization, potentially distorting individual effect size estimates and compromising overall…
Alexander Volkmann
Recently, the variability ratio (VR) effect size statistic has been used with increasing frequency in the study of differences in variation of a measured variable between two study populations. More specifically, the VR effect size statistic allows for the detection of treatment effect heterogeneity (TEH) of medical…
Bürki Audrey, Shravan Vasishth
language production Authors: ['Bürki Audrey' 'Shravan Vasishth'] With the pandemic, many experimental psychologists/linguists have started to collect data over the internet (hereafter "on-line data"). The feasibility of such experiments and the sample sizes required to achieve sufficient statistical power in future…
Felix Holzmeister, Magnus Johannesson, Robert Böhm, Anna Dreber + 2 more
'Jürgen Huber' 'Michael Kirchler'] Title: Significance In conducting empirical research in the social sciences, the results of testing the same hypothesis can vary depending on the population sampled, the study design, and the analysis. Such variation, referred to as heterogeneity, limits the generalizability of…
Andrew Gelman, Amy Krefman, Lauren Kennedy, Jessica Hullman
When designing and evaluating an experiment or observational study, it is useful to have a realistic hypothesis regarding the average treatment effect. We present an approach to conceptualizing this average by first considering a distribution of effects. We demonstrate with examples in medicine, economics, and…
Krzysztof Cipora, Guilherme Wood
The Spatial Numerical Association of Response Codes (SNARC) effect describes a stimulus-response association of left with small magnitude and right with large magnitude. Usually, it is estimated by means of regression slopes, where the independent variable only has a limited number of levels. Inspection of the…
Satoshi Aoki, Motomi Itô, Masakazu Shimada
Hedges' d, an existing unbiased effect size of the difference between means, assumes the variance equality. However, the assumption of the variance equality is fragile, and is often violated in practical applications. Here, we define e, a new effect size of the difference between means, which does not assume the…
Joseph F. Mudge, Leanne F. Baker, Christopher B. Edge, Jeff E. Houlahan + 1 more
'Jeff E. Houlahan' 'Zheng Su'] Null hypothesis significance testing has been under attack in recent years, partly owing to the arbitrary nature of setting α (the decision-making threshold and probability of Type I error) at a constant value, usually 0.05. If the goal of null hypothesis testing is to present conclusions…
Zac P. Robinson, James Steele, Eric R. Helms, Eric T. Trexler + 8 more
There is growing emphasis on investigating heterogeneity in resistance training (RT) outcomes, likely motivated by observations of substantial gross variability in training effects. However, gross variability does not necessarily represent true inter-individual response variation (IRV) and can be obscured by…
Joshua F. Wiley, Bei Bei, John Trinder, Rachel Manber
Whilst most psychological research focuses on differences in means, a growing body of literature demonstrates the value of considering differences in intra-individual variability. Compared to the number of methods available for analyzing mean differences, there is a paucity of methods available for analyzing…
Amelia C. Warden, Jessica K. Witt, Mengzhu Fu, Michael D. Dodd
Studies have shown that people can derive summary statistics - such as the mean - from sets of similar objects for low-level (orientation, color value), mid-level (size), and high-level visual features (emotional expression) through the phenomena of ensemble perception. Recent research has identified a bias to…
Dobromir Rahnev
Many studies have shown that confidence and accuracy can be dissociated in a variety of tasks. However, most of these dissociations involve small effect sizes, occur only in a subset of participants, and include a reaction time (RT) confound. Here, I develop a new method for inducing confidence-accuracy dissociations…
Gang Chen, Daniel S. Pine, Melissa A. Brotman, Ashley R. Smith + 3 more
Big data initiatives have gained popularity for leveraging a large sample of subjects to study a wide range of effect magnitudes in the brain. On the other hand, most task-based FMRI designs feature relatively small number of subjects, so that resulting parameter estimates may be associated with compromised precision.…
Marco Cardis, Maura Casadio, Rajiv Ranganathan
Motor variability plays an important role in motor learning, although the exact mechanisms of how variability affects learning is not well understood. Recent evidence suggests that motor variability may have different effects on learning in redundant tasks, depending on whether it is present in the task space (where it…
Farid Anvari, Noëlle Z. Rensing, Elise K. Kalokerinos, Richard E. Lucas + 1 more
'Richard E. Lucas' 'Iris K. Schneider'] Within-person variability in affect (e.g., Neuroticism) and personality have been linked to well-being. These are measured either by asking people to report how variable they are or to give multiple reports on the construct and calculating a within-person standard deviation…
M. Pahlevani
The variance, the average of squared deviations of data values from their mean, is the most widely used criterion for measuring the variation. Small amounts of the variance indicate that the values tend to be close to the mean and its high amounts are indicative of more dispersion around the mean. However, when dealing…
Authors not listed
Physics-based methods such as protein-ligand binding free energy calculations have been increasingly adopted in early-stage drug discovery to prioritize promising compounds for synthesis. However, the accuracy of these methods is highly dependent on details of the calculation and choices made while preparing the…
Authors not listed
Optimizing the synthesis conditions of advanced materials is challenging, especially when outcomes are subject to inherent experimental uncertainties. Bayesian optimization is a popular tool for accelerating materials discovery, but its standard risk-neutral framework overlooks the variability of outcomes under…
Marlou Nadine Perquin, Tobias Heed, Christoph Kayser
Any series of sensorimotor actions shows fluctuations in speed and accuracy from repetition to repetition, even when the sensory input and motor output requirements remain identical over time. Such fluctuations are particularly prominent in reaction time (RT) series from laboratory neurocognitive tasks. Despite their…
Marina Gorostiola González, Olivier J. M. Béquignon, Emma Manners, Anna Gaulton + 7 more
Bioactivity prediction is essential in computational drug discovery, particularly within virtual screening campaigns. Despite advancements in model architectures and features, the sparsity and quality of relevant training data remain a major bottleneck. Notably, genetic variance annotation, crucial for understanding…
Zhenghao Wu, Tianhang Zhou
In the realm of multiscale molecular simulations, structure-based coarse graining is a prominent approach for creating efficient coarse-grained (CG) representations of soft matter systems such as polymers. This involves optimizing CG interactions by matching static correlation functions of corresponding degrees of…
Simon Iveson, Kevin Galvin
This paper presents a simple relationship for estimating the uncertainty in the overall yield and species recovery when the two-product formula is applied to assays of the feed, product and tailings streams of a steady-state mineral separator. The non-linearity of the two-product formula means the reliability of these…