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Replicability, robustness, and reproducibility in psychological science
Replication—an important, uncommon, and misunderstood practice—is gaining
appreciation in psychology. Achieving replicability is important for making research …
appreciation in psychology. Achieving replicability is important for making research …
Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence
Most neuroscientists would agree that for brain research to progress, we have to know which
experimental manipulations have no effect as much as we must identify those that do have …
experimental manipulations have no effect as much as we must identify those that do have …
Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization
Sex plays a crucial role in human brain development, aging, and the manifestation of
psychiatric and neurological disorders. However, our understanding of sex differences in …
psychiatric and neurological disorders. However, our understanding of sex differences in …
Small effects: The indispensable foundation for a cumulative psychological science
We draw on genetics research to argue that complex psychological phenomena are most
likely determined by a multitude of causes and that any individual cause is likely to have …
likely determined by a multitude of causes and that any individual cause is likely to have …
Indices of effect existence and significance in the Bayesian framework
Turmoil has engulfed psychological science. Causes and consequences of the
reproducibility crisis are in dispute. With the hope of addressing some of its aspects …
reproducibility crisis are in dispute. With the hope of addressing some of its aspects …
Estimating power in (generalized) linear mixed models: An open introduction and tutorial in R
Mixed-effects models are a powerful tool for modeling fixed and random effects
simultaneously, but do not offer a feasible analytic solution for estimating the probability that …
simultaneously, but do not offer a feasible analytic solution for estimating the probability that …
What is the test-retest reliability of common task-functional MRI measures? New empirical evidence and a meta-analysis
Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability
to identify meaningful biomarkers is limited by measurement reliability; unreliable measures …
to identify meaningful biomarkers is limited by measurement reliability; unreliable measures …
[HTML][HTML] Dump the “dimorphism”: Comprehensive synthesis of human brain studies reveals few male-female differences beyond size
L Eliot, A Ahmed, H Khan, J Patel - Neuroscience & Biobehavioral Reviews, 2021 - Elsevier
With the explosion of neuroimaging, differences between male and female brains have been
exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem …
exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem …
How many participants do we have to include in properly powered experiments? A tutorial of power analysis with reference tables
M Brysbaert - Journal of cognition, 2019 - pmc.ncbi.nlm.nih.gov
Given that an effect size of d=. 4 is a good first estimate of the smallest effect size of interest
in psychological research, we already need over 50 participants for a simple comparison of …
in psychological research, we already need over 50 participants for a simple comparison of …
Effect size guidelines, sample size calculations, and statistical power in gerontology
CR Brydges - Innovation in aging, 2019 - academic.oup.com
Abstract Background and Objectives Researchers typically use Cohen's guidelines of
Pearson'sr=. 10,. 30, and. 50, and Cohen'sd= 0.20, 0.50, and 0.80 to interpret observed …
Pearson'sr=. 10,. 30, and. 50, and Cohen'sd= 0.20, 0.50, and 0.80 to interpret observed …