G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences
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TLDR
G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested.Abstract:
G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of thet, F, and χ2 test families. In addition, it includes power analyses forz tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.read more
Citations
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Journal ArticleDOI
Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
TL;DR: In the new version, procedures to analyze the power of tests based on single-sample tetrachoric correlations, comparisons of dependent correlations, bivariate linear regression, multiple linear regression based on the random predictor model, logistic regression, and Poisson regression are added.
Journal ArticleDOI
Power failure: why small sample size undermines the reliability of neuroscience
Katherine S. Button,John P. A. Ioannidis,Claire Mokrysz,Brian A. Nosek,Jonathan Flint,Emma S J Robinson,Marcus R. Munafò +6 more
TL;DR: It is shown that the average statistical power of studies in the neurosciences is very low, and the consequences include overestimates of effect size and low reproducibility of results.
Journal ArticleDOI
Neurotoxic reactive astrocytes are induced by activated microglia
Shane A. Liddelow,Kevin A. Guttenplan,Laura E. Clarke,Frederick C. Bennett,Christopher J. Bohlen,Lucas Schirmer,Mariko L. Bennett,Alexandra E. Münch,Won-Suk Chung,Todd C. Peterson,Daniel K. Wilton,Arnaud Frouin,Brooke A. Napier,Nikhil Panicker,Manoj Kumar,Marion S. Buckwalter,David H. Rowitch,Valina L. Dawson,Ted M. Dawson,Beth Stevens,Ben A. Barres +20 more
TL;DR: It is shown that activated microglia induce A1 astrocytes by secreting Il-1α, TNF and C1q, and that these cytokines together are necessary and sufficient to induce A2 astroCytes, which are abundant in various human neurodegenerative diseases.
MonographDOI
The essential guide to effect sizes : statistical power, meta-analysis, and the interpretation of research results
TL;DR: This book discusses effect sizes, meta-Analysis, and the interpretation of results in the context of meta-analysis, which addresses the role of sample sizes in the analysis of power research.
Journal ArticleDOI
Attentive Turkers: MTurk participants perform better on online attention checks than do subject pool participants
David J. Hauser,Norbert Schwarz +1 more
TL;DR: In three online studies, participants from MTurk and collegiate populations participated in a task that included a measure of attentiveness to instructions (an instructional manipulation check: IMC), and MTurkers were more attentive to the instructions than were college students, even on novel IMCs.
References
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Book
Statistical Power Analysis for the Behavioral Sciences
TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Book
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Statistical Methods for Rates and Proportions
R. L. Plackett,Joseph L. Fleiss +1 more
Book
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TL;DR: Within-subject and mixed designs of Factorial Design have been studied in this article, where the Principal Two-Factor Within-Factor Effects and Simple Effects have been used to estimate the effect size and power of interaction components.