Journal ArticleDOI
Sample-Size Planning for More Accurate Statistical Power: A Method Adjusting Sample Effect Sizes for Publication Bias and Uncertainty.
TLDR
This work presents an alternative approach that adjusts sample effect sizes for bias and uncertainty, and it is demonstrated its effectiveness for several experimental designs.Abstract:
The sample size necessary to obtain a desired level of statistical power depends in part on the population value of the effect size, which is, by definition, unknown. A common approach to sample-size planning uses the sample effect size from a prior study as an estimate of the population value of the effect to be detected in the future study. Although this strategy is intuitively appealing, effect-size estimates, taken at face value, are typically not accurate estimates of the population effect size because of publication bias and uncertainty. We show that the use of this approach often results in underpowered studies, sometimes to an alarming degree. We present an alternative approach that adjusts sample effect sizes for bias and uncertainty, and we demonstrate its effectiveness for several experimental designs. Furthermore, we discuss an open-source R package, BUCSS, and user-friendly Web applications that we have made available to researchers so that they can easily implement our suggested methods.read more
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Journal ArticleDOI
How Many Participants Do We Have to Include in Properly Powered Experiments? A Tutorial of Power Analysis with Reference Tables.
TL;DR: In this article, the authors describe reference numbers needed for the designs most often used by psychologists, including single-variable between-groups and repeated-measures designs with two and three levels, two-factor designs involving two repeated measures and one repeated measure, and split-plot design.
Posted ContentDOI
Sample Size Justification
TL;DR: In this paper, six approaches are discussed to justify the sample size in a quantitative empirical study: collecting data from (an) almost) the entire population, choosing a sample size based on resource constraints, performing an a-priori power analysis, planning for a desired accuracy, using heuristics, or explicitly acknowledging the absence of a justification.
Journal ArticleDOI
A practical primer to power analysis for simple experimental designs
TL;DR: In this paper, the focus is on applications of power analysis for experimental designs often encountered in psychology, starting from simple two-group independent and paired groups and moving to one-way analysis of variance, factorial designs, contrast analysis, trend analysis, regression analysis, analysis of covariance, and mediation analysis.
Journal ArticleDOI
Resting-state functional brain connectivity best predicts the personality dimension of openness to experience.
TL;DR: Openness to experience emerged as the only reliably predicted personality factor and was derived from a principal components analysis of the Neuroticism/Extraversion/Openness Five-Factor Inventory factor scores, thereby reducing noise and enhancing the precision of these measures of personality.
Journal ArticleDOI
Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis.
TL;DR: Examination of evidence of publication bias in a large-scale data set of primary studies that were included in 83 meta-analyses published in Psychological Bulletin and 499 systematic reviews from the Cochrane Database of Systematic Reviews found evidence of publications bias that appeared to be similar in both psychology and medicine.
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.
Journal ArticleDOI
G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences
TL;DR: 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.
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
Estimating the reproducibility of psychological science
Alexander A. Aarts,Joanna E. Anderson,Christopher J. Anderson,Peter Raymond Attridge,Peter Raymond Attridge,Angela S. Attwood,Jordan Axt,Molly Babel,Štěpán Bahník,Erica Baranski,Michael Barnett-Cowan,Elizabeth Bartmess,Jennifer S. Beer,Raoul Bell,Heather Bentley,Leah Beyan,Grace Binion,Grace Binion,Denny Borsboom,Annick Bosch,Frank A. Bosco,Sara Bowman,Mark J. Brandt,Erin L Braswell,Hilmar Brohmer,Benjamin T. Brown,Kristina G. Brown,Jovita Brüning,Jovita Brüning,Ann Calhoun-Sauls,Shannon P. Callahan,Elizabeth Chagnon,Jesse Chandler,Jesse Chandler,Christopher R. Chartier,Felix Cheung,Felix Cheung,Cody D. Christopherson,Linda Cillessen,Russ Clay,Hayley M. D. Cleary,Mark D. Cloud,Michael Conn,Johanna Cohoon,Simon Columbus,Andreas Cordes,Giulio Costantini,Leslie Cramblet Alvarez,Ed Cremata,Jan Crusius,Jamie DeCoster,Michelle A. DeGaetano,Nicolás Delia Penna,Bobby Den Bezemer,Marie K. Deserno,Olivia Devitt,Laura Dewitte,David G. Dobolyi,Geneva T. Dodson,M. Brent Donnellan,Ryan Donohue,Rebecca A. Dore,Angela Rachael Dorrough,Angela Rachael Dorrough,Anna Dreber,Michelle Dugas,Elizabeth W. Dunn,Kayleigh E Easey,Sylvia Eboigbe,Casey Eggleston,Jo Embley,Sacha Epskamp,Timothy M. Errington,Vivien Estel,Frank J. Farach,Jenelle Feather,Anna Fedor,Belén Fernández-Castilla,Susann Fiedler,James G. Field,Stanka A. Fitneva,Taru Flagan,Amanda L. Forest,Eskil Forsell,Joshua D. Foster,Michael C. Frank,Rebecca S. Frazier,Heather M. Fuchs,Philip A. Gable,Jeff Galak,Elisa Maria Galliani,Anup Gampa,Sara García,Douglas Gazarian,Elizabeth Gilbert,Roger Giner-Sorolla,Andreas Glöckner,Andreas Glöckner,Lars Goellner,Jin X. Goh,Rebecca M. Goldberg,Patrick T. Goodbourn,Shauna Gordon-McKeon,Bryan Gorges,Jessie Gorges,Justin Goss,Jesse Graham,James A. Grange,Jeremy R. Gray,Chris H.J. Hartgerink,Joshua K. Hartshorne,Fred Hasselman,Timothy Hayes,Emma Heikensten,Felix Henninger,Felix Henninger,John Hodsoll,Taylor Holubar,Gea Hoogendoorn,Denise J. Humphries,Cathy On-Ying Hung,Nathali Immelman,Vanessa C. Irsik,Georg Jahn,Frank Jäkel,Marc Jekel,Magnus Johannesson,Larissa Gabrielle Johnson,David J. Johnson,Kate M. Johnson,William J. Johnston,Kai J. Jonas,Jennifer A. Joy-Gaba,Heather Barry Kappes,Kim Kelso,Mallory C. Kidwell,Seung K. Kim,Matthew W. Kirkhart,Bennett Kleinberg,Bennett Kleinberg,Goran Knežević,Franziska Maria Kolorz,Jolanda J. Kossakowski,Robert Krause,Job Krijnen,Tim Kuhlmann,Yoram K. Kunkels,Megan M. Kyc,Calvin K. Lai,Aamir Laique,Daniel Lakens,Kristin A. Lane,Bethany Lassetter,Ljiljana B. Lazarević,Etienne P. Le Bel,Key Jung Lee,Minha Lee,Kristi M. Lemm,Carmel A. Levitan,Melissa Lewis,Lin Lin,Stephanie C. Lin,Matthias Lippold,Darren Loureiro,Ilse Luteijn,Sean P. Mackinnon,Heather N. Mainard,Denise C. Marigold,Daniel P. Martin,Tylar Martinez,E. J. Masicampo,Joshua J. Matacotta,Maya B. Mathur,Michael May,Michael May,Nicole Mechin,Pranjal H. Mehta,Johannes M. Meixner,Johannes M. Meixner,Alissa Melinger,Jeremy K. Miller,Mallorie Miller,Katherine Moore,Katherine Moore,Marcus Möschl,Matt Motyl,Stephanie M. Müller,Marcus R. Munafò,Koen Ilja Neijenhuijs,Taylor Nervi,Gandalf Nicolas,Gustav Nilsonne,Gustav Nilsonne,Brian A. Nosek,Brian A. Nosek,Michèle B. Nuijten,Catherine Olsson,Catherine Olsson,Colleen Osborne,Lutz Ostkamp,Misha Pavel,Ian S. Penton-Voak,Olivia Perna,Cyril Pernet,Marco Perugini,R. Nathan Pipitone,Michael C. Pitts,Franziska Plessow,Franziska Plessow,Jason M. Prenoveau,Rima-Maria Rahal,Rima-Maria Rahal,Kate A. Ratliff,David Reinhard,Frank Renkewitz,Ashley A. Ricker,Anastasia E. Rigney,Andrew M Rivers,Mark A. Roebke,Abraham M. Rutchick,Robert S. Ryan,Onur Sahin,Anondah R. Saide,Gillian M. Sandstrom,David Santos,David Santos,Rebecca Saxe,René Schlegelmilch,René Schlegelmilch,Kathleen Schmidt,Sabine Scholz,Larissa Seibel,Dylan Selterman,Samuel Shaki,William B. Simpson,H. Colleen Sinclair,Jeanine L. M. Skorinko,Agnieszka Slowik,Joel S. Snyder,Courtney K. Soderberg,Carina Sonnleitner,Nick Spencer,Jeffrey R. Spies,Sara Steegen,Stefan Stieger,Nina Strohminger,Gavin Brent Sullivan,Thomas Talhelm,Megan Tapia,Anniek M. te Dorsthorst,Manuela Thomae,Manuela Thomae,Sarah L. Thomas,Pia Tio,Frits Traets,Steve N.H. Tsang,Francis Tuerlinckx,Paul J. Turchan,Milan Valášek,Anna E. Van't Veer,Robbie C. M. van Aert,Marcel A.L.M. van Assen,Riet van Bork,Mathijs Van De Ven,Don van den Bergh,Marije van der Hulst,Roel van Dooren,Johnny van Doorn,Daan R. van Renswoude,Hedderik van Rijn,Wolf Vanpaemel,Alejandro Vásquez Echeverría,Melissa Vazquez,Natalia Vélez,Marieke Vermue,Mark Verschoor,Michelangelo Vianello,Martin Voracek,Gina Vuu,Eric-Jan Wagenmakers,Joanneke Weerdmeester,Ashlee Welsh,Erin C. Westgate,Joeri Wissink,Michael J. Wood,Andy T. Woods,Andy T. Woods,Emily M. Wright,Sining Wu,Marcel Zeelenberg,Kellylynn Zuni +290 more
TL;DR: A large-scale assessment suggests that experimental reproducibility in psychology leaves a lot to be desired, and correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
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