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3. Correction: Data Sharing Goals for Nonprofit Funders of Clinical Trials.

Author

Coetzee, Timothy, Ball, Mad Price, Boutin, Marc, Bronson, Abby, Dexter, David T, English, Rebecca A, Furlong, Patricia, Goodman, Andrew D, Grossman, Cynthia, Hernandez, Adrian F, Hinners, Jennifer E, Hudson, Lynn, Kennedy, Annie, Marchisotto, Mary Jane, Matrisian, Lynn, Myers, Elizabeth, Nowell, W Benjamin, Nosek, Brian A, Sherer, Todd, Shore, Carolyn, Sim, Ida, Smolensky, Luba, Williams, Christopher, Wood, Julie, and Terry, Sharon F

Abstract

[This corrects the article DOI: 10.2196/23011.].

Published
2021

4. Meta-Analytic Use of Balanced Identity Theory to Validate the Implicit Association Test

Author

Cvencek, Dario, Meltzoff, Andrew N, Maddox, Craig D, Nosek, Brian A, Rudman, Laurie A, Devos, Thierry, Dunham, Yarrow, Baron, Andrew S, Steffens, Melanie C, Lane, Kristin, Horcajo, Javier, Ashburn-Nardo, Leslie, Quinby, Amanda, Srivastava, Sameer B, Schmidt, Kathleen, Aidman, Eugene, Tang, Emilie, Farnham, Shelly, Mellott, Deborah S, Banaji, Mahzarin R, and Greenwald, Anthony G

Subjects
Clinical and Health Psychology, Psychology, Behavioral and Social Science, Attitude, Female, Humans, Male, Models, Psychological, Reproducibility of Results, Self Concept, Self Report, Social Identification, Statistics as Topic, Stereotyping, attitudes, stereotypes, identity, self-esteem, Implicit Association Test, Cognitive Sciences, Social Psychology, Social and personality psychology
Abstract

This meta-analysis evaluated theoretical predictions from balanced identity theory (BIT) and evaluated the validity of zero points of Implicit Association Test (IAT) and self-report measures used to test these predictions. Twenty-one researchers contributed individual subject data from 36 experiments (total N = 12,773) that used both explicit and implicit measures of the social-cognitive constructs. The meta-analysis confirmed predictions of BIT's balance-congruity principle and simultaneously validated interpretation of the IAT's zero point as indicating absence of preference between two attitude objects. Statistical power afforded by the sample size enabled the first confirmations of balance-congruity predictions with self-report measures. Beyond these empirical results, the meta-analysis introduced a within-study statistical test of the balance-congruity principle, finding that it had greater efficiency than the previous best method. The meta-analysis's full data set has been publicly archived to enable further studies of interrelations among attitudes, stereotypes, and identities.

Published
2021

5. Consensus-based guidance for conducting and reporting multi-analyst studies

Author

Aczel, Balazs, Szaszi, Barnabas, Nilsonne, Gustav, van den Akker, Olmo R, Albers, Casper J, van Assen, Marcel ALM, Bastiaansen, Jojanneke A, Benjamin, Daniel, Boehm, Udo, Botvinik-Nezer, Rotem, Bringmann, Laura F, Busch, Niko A, Caruyer, Emmanuel, Cataldo, Andrea M, Cowan, Nelson, Delios, Andrew, van Dongen, Noah NN, Donkin, Chris, van Doorn, Johnny B, Dreber, Anna, Dutilh, Gilles, Egan, Gary F, Gernsbacher, Morton Ann, Hoekstra, Rink, Hoffmann, Sabine, Holzmeister, Felix, Huber, Juergen, Johannesson, Magnus, Jonas, Kai J, Kindel, Alexander T, Kirchler, Michael, Kunkels, Yoram K, Lindsay, D Stephen, Mangin, Jean-Francois, Matzke, Dora, Munafò, Marcus R, Newell, Ben R, Nosek, Brian A, Poldrack, Russell A, van Ravenzwaaij, Don, Rieskamp, Jörg, Salganik, Matthew J, Sarafoglou, Alexandra, Schonberg, Tom, Schweinsberg, Martin, Shanks, David, Silberzahn, Raphael, Simons, Daniel J, Spellman, Barbara A, St-Jean, Samuel, Starns, Jeffrey J, Uhlmann, Eric Luis, Wicherts, Jelte, and Wagenmakers, Eric-Jan

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Health Sciences, Consensus, Data Analysis, Datasets as Topic, Research, multi-analyst, metascience, statistical practice, science forum, expert consensus, analytical variability, None, medicine, neuroscience, none, Biochemistry and Cell Biology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.

Published
2021

6. A randomized trial of a lab-embedded discourse intervention to improve research ethics

Author

Plemmons, Dena K, Baranski, Erica N, Harp, Kyle, Lo, David D, Soderberg, Courtney K, Errington, Timothy M, Nosek, Brian A, and Esterling, Kevin M

Subjects
Philosophy and Religious Studies, Applied Ethics, Clinical Research, Behavioral and Social Science, Clinical Trials and Supportive Activities, Quality Education, research ethics, randomized trial, authorship, data management
Abstract

We report a randomized trial of a research ethics training intervention designed to enhance ethics communication in university science and engineering laboratories, focusing specifically on authorship and data management. The intervention is a project-based research ethics curriculum that was designed to enhance the ability of science and engineering research laboratory members to engage in reason giving and interpersonal communication necessary for ethical practice. The randomized trial was fielded in active faculty-led laboratories at two US research-intensive institutions. Here, we show that laboratory members perceived improvements in the quality of discourse on research ethics within their laboratories and enhanced awareness of the relevance and reasons for that discourse for their work as measured by a survey administered over 4 mo after the intervention. This training represents a paradigm shift compared with more typical module-based or classroom ethics instruction that is divorced from the everyday workflow and practices within laboratories and is designed to cultivate a campus culture of ethical science and engineering research in the very work settings where laboratory members interact.

Published
2020

8. Redefine statistical significance.

Author

Benjamin, Daniel J, Berger, James O, Johannesson, Magnus, Nosek, Brian A, Wagenmakers, E-J, Berk, Richard, Bollen, Kenneth A, Brembs, Björn, Brown, Lawrence, Camerer, Colin, Cesarini, David, Chambers, Christopher D, Clyde, Merlise, Cook, Thomas D, De Boeck, Paul, Dienes, Zoltan, Dreber, Anna, Easwaran, Kenny, Efferson, Charles, Fehr, Ernst, Fidler, Fiona, Field, Andy P, Forster, Malcolm, George, Edward I, Gonzalez, Richard, Goodman, Steven, Green, Edwin, Green, Donald P, Greenwald, Anthony G, Hadfield, Jarrod D, Hedges, Larry V, Held, Leonhard, Hua Ho, Teck, Hoijtink, Herbert, Hruschka, Daniel J, Imai, Kosuke, Imbens, Guido, Ioannidis, John PA, Jeon, Minjeong, Jones, James Holland, Kirchler, Michael, Laibson, David, List, John, Little, Roderick, Lupia, Arthur, Machery, Edouard, Maxwell, Scott E, McCarthy, Michael, Moore, Don A, Morgan, Stephen L, Munafó, Marcus, Nakagawa, Shinichi, Nyhan, Brendan, Parker, Timothy H, Pericchi, Luis, Perugini, Marco, Rouder, Jeff, Rousseau, Judith, Savalei, Victoria, Schönbrodt, Felix D, Sellke, Thomas, Sinclair, Betsy, Tingley, Dustin, Van Zandt, Trisha, Vazire, Simine, Watts, Duncan J, Winship, Christopher, Wolpert, Robert L, Xie, Yu, Young, Cristobal, Zinman, Jonathan, and Johnson, Valen E

Subjects
Data Interpretation, Statistical, Models, Statistical, Reproducibility of Results, Scholarly Communication
Abstract

We propose to change the default P-value threshold for statistical significance for claims of new discoveries from 0.05 to 0.005.

Published
2018

10. Observe, hypothesize, test, repeat: Luttrell, Petty and Xu (2017) demonstrate good science

Author

Ebersole, Charles R, Alaei, Ravin, Atherton, Olivia E, Bernstein, Michael J, Brown, Mitch, Chartier, Christopher R, Chung, Lisa Y, Hermann, Anthony D, Joy-Gaba, Jennifer A, Line, Marsha J, Rule, Nicholas O, Sacco, Donald F, Vaughn, Leigh Ann, and Nosek, Brian A

Subjects
Psychology, Applied and Developmental Psychology, Cognitive Sciences, Social Psychology, Social and personality psychology
Published
2017

11. Many Labs 3: Evaluating participant pool quality across the academic semester via replication

Author

Ebersole, Charles R, Atherton, Olivia E, Belanger, Aimee L, Skulborstad, Hayley M, Allen, Jill M, Banks, Jonathan B, Baranski, Erica, Bernstein, Michael J, Bonfiglio, Diane BV, Boucher, Leanne, Brown, Elizabeth R, Budiman, Nancy I, Cairo, Athena H, Capaldi, Colin A, Chartier, Christopher R, Chung, Joanne M, Cicero, David C, Coleman, Jennifer A, Conway, John G, Davis, William E, Devos, Thierry, Fletcher, Melody M, German, Komi, Grahe, Jon E, Hermann, Anthony D, Hicks, Joshua A, Honeycutt, Nathan, Humphrey, Brandon, Janus, Matthew, Johnson, David J, Joy-Gaba, Jennifer A, Juzeler, Hannah, Keres, Ashley, Kinney, Diana, Kirshenbaum, Jacqeline, Klein, Richard A, Lucas, Richard E, Lustgraaf, Christopher JN, Martin, Daniel, Menon, Madhavi, Metzger, Mitchell, Moloney, Jaclyn M, Morse, Patrick J, Prislin, Radmila, Razza, Timothy, Re, Daniel E, Rule, Nicholas O, Sacco, Donald F, Sauerberger, Kyle, Shrider, Emily, Shultz, Megan, Siemsen, Courtney, Sobocko, Karin, Sternglanz, R Weylin, Summerville, Amy, Tskhay, Konstantin O, van Allen, Zack, Vaughn, Leigh Ann, Walker, Ryan J, Weinberg, Ashley, Wilson, John Paul, Wirth, James H, Wortman, Jessica, and Nosek, Brian A

Subjects
Biological Psychology, Psychology, Clinical Research, Behavioral and Social Science, Social psychology, Cognitive psychology, Replication, Participant pool, Individual differences, Sampling effects, Situational effects, Cognitive Sciences, Social Psychology, Social and personality psychology
Abstract

The university participant pool is a key resource for behavioral research, and data quality is believed to vary over the course of the academic semester. This crowdsourced project examined time of semester variation in 10 known effects, 10 individual differences, and 3 data quality indicators over the course of the academic semester in 20 participant pools (N = 2696) and with an online sample (N = 737). Weak time of semester effects were observed on data quality indicators, participant sex, and a few individual differences—conscientiousness, mood, and stress. However, there was little evidence for time of semester qualifying experimental or correlational effects. The generality of this evidence is unknown because only a subset of the tested effects demonstrated evidence for the original result in the whole sample. Mean characteristics of pool samples change slightly during the semester, but these data suggest that those changes are mostly irrelevant for detecting effects.

Published
2016

12. Reducing Implicit Racial Preferences: II. Intervention Effectiveness Across Time

Author

Lai, Calvin K, Skinner, Allison L, Cooley, Erin, Murrar, Sohad, Brauer, Markus, Devos, Thierry, Calanchini, Jimmy, Xiao, Y Jenny, Pedram, Christina, Marshburn, Christopher K, Simon, Stefanie, Blanchar, John C, Joy-Gaba, Jennifer A, Conway, John, Redford, Liz, Klein, Rick A, Roussos, Gina, Schellhaas, Fabian MH, Burns, Mason, Hu, Xiaoqing, McLean, Meghan C, Axt, Jordan R, Asgari, Shaki, Schmidt, Kathleen, Rubinstein, Rachel, Marini, Maddalena, Rubichi, Sandro, Shin, Jiyun-Elizabeth L, and Nosek, Brian A

Subjects
Clinical and Health Psychology, Psychology, Clinical Research, Adolescent, Female, Humans, Male, Motivation, Prejudice, Racial Groups, Stereotyping, Young Adult, attitudes, Implicit Association Test, implicit social cognition, malleability, racial prejudice, Cognitive Sciences, Experimental Psychology
Abstract

Implicit preferences are malleable, but does that change last? We tested 9 interventions (8 real and 1 sham) to reduce implicit racial preferences over time. In 2 studies with a total of 6,321 participants, all 9 interventions immediately reduced implicit preferences. However, none were effective after a delay of several hours to several days. We also found that these interventions did not change explicit racial preferences and were not reliably moderated by motivations to respond without prejudice. Short-term malleability in implicit preferences does not necessarily lead to long-term change, raising new questions about the flexibility and stability of implicit preferences. (PsycINFO Database Record

Published
2016

13. How open science helps researchers succeed

Author

McKiernan, Erin C, Bourne, Philip E, Brown, C Titus, Buck, Stuart, Kenall, Amye, Lin, Jennifer, McDougall, Damon, Nosek, Brian A, Ram, Karthik, Soderberg, Courtney K, Spies, Jeffrey R, Thaney, Kaitlin, Updegrove, Andrew, Woo, Kara H, and Yarkoni, Tal

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Health Sciences, Access to Information, Open Access Publishing, Research, Research Personnel, none, open access, open data, open science, open source, research, Biochemistry and Cell Biology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Open access, open data, open source and other open scholarship practices are growing in popularity and necessity. However, widespread adoption of these practices has not yet been achieved. One reason is that researchers are uncertain about how sharing their work will affect their careers. We review literature demonstrating that open research is associated with increases in citations, media attention, potential collaborators, job opportunities and funding opportunities. These findings are evidence that open research practices bring significant benefits to researchers relative to more traditional closed practices.

Published
2016

14. High replicability of newly discovered social-behavioural findings is achievable

Author

Protzko, John, primary, Krosnick, Jon, additional, Nelson, Leif, additional, Nosek, Brian A., additional, Axt, Jordan, additional, Berent, Matt, additional, Buttrick, Nicholas, additional, DeBell, Matthew, additional, Ebersole, Charles R., additional, Lundmark, Sebastian, additional, MacInnis, Bo, additional, O’Donnell, Michael, additional, Perfecto, Hannah, additional, Pustejovsky, James E., additional, Roeder, Scott S., additional, Walleczek, Jan, additional, and Schooler, Jonathan W., additional

Published
2023
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17. Promoting Open Science to Increase the Trustworthiness of Evidence in Special Education

Author

Cook, Bryan G., Lloyd, John Wills, Mellor, David, Nosek, Brian A., and Therrien, William J.

Abstract

Scientific evidence should guide the selection of practice for individuals with disabilities. Scientific evidence, however, must be trustworthy to move special education toward greater empirical certainty and more effective policies and practices. Transparency, openness, and reproducibility increase the trustworthiness of evidence. We propose that researchers in special education adopt emerging open-science reforms, such as preprints, data and materials sharing, preregistration of studies and analysis plans, and Registered Reports. Adoption of these practices will require shifts in cultural norms, guidelines, and incentives. We discuss how adopting open-science practices can advance the quality of research and, consequently, policy and practice in special education.

Published
2018
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18. Implicit Bias

Author

Banaji, Mahzarin, primary, Greenwald, Anthony, additional, and Nosek, Brian, additional

Published
2021
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19. Scientific Utopia: II. Restructuring incentives and practices to promote truth over publishability

Author

Nosek, Brian A., Spies, Jeffrey R., and Motyl, Matt

Subjects
Physics - Physics and Society, Computer Science - Digital Libraries
Abstract

An academic scientist's professional success depends on publishing. Publishing norms emphasize novel, positive results. As such, disciplinary incentives encourage design, analysis, and reporting decisions that elicit positive results and ignore negative results. Prior reports demonstrate how these incentives inflate the rate of false effects in published science. When incentives favor novelty over replication, false results persist in the literature unchallenged, reducing efficiency in knowledge accumulation. Previous suggestions to address this problem are unlikely to be effective. For example, a journal of negative results publishes otherwise unpublishable reports. This enshrines the low status of the journal and its content. The persistence of false findings can be meliorated with strategies that make the fundamental but abstract accuracy motive - getting it right - competitive with the more tangible and concrete incentive - getting it published. We develop strategies for improving scientific practices and knowledge accumulation that account for ordinary human motivations and self-serving biases., Comment: 41 pages, 1 table

Published
2012

20. Scientific Utopia: I. Opening scientific communication

Author

Nosek, Brian A. and Bar-Anan, Yoav

Subjects
Physics - Physics and Society, Computer Science - Digital Libraries
Abstract

Existing norms for scientific communication are rooted in anachronistic practices of bygone eras, making them needlessly inefficient. We outline a path that moves away from the existing model of scientific communication to improve the efficiency in meeting the purpose of public science - knowledge accumulation. We call for six changes: (1) full embrace of digital communication, (2) open access to all published research, (3) disentangling publication from evaluation, (4) breaking the "one article, one journal" model with a grading system for evaluation and diversified dissemination outlets, (5) publishing peer review, and, (6) allowing open, continuous peer review. We address conceptual and practical barriers to change, and provide examples showing how the suggested practices are being used already. The critical barriers to change are not technical or financial; they are social. While scientists guard the status quo, they also have the power to change it., Comment: Psychological Inquiry, 2012

Published
2012

27. 10 July 2023 (Day 1) Panel 1b: Analysis of open science policies

Author

Tananbaum, Greg, Arentoft, Michael, Greenberg, Josh, Hanisch, Bob, Joseph, Heather, Mchunu, Nokuthula, and Nosek, Brian

Abstract

CERN/NASA “Accelerating the Adoption of Open Science”, from July 10th-14th at CERN in Geneva, Switzerland https://indico.cern.ch/event/1254282/ 10 July 2023 (Day 1)Strategic Plans and Policies Watch the recording of this contribution here:https://cds.cern.ch/record/2864963

Published
2023
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28. Make scientific data FAIR

Author

Stall, Shelley, Yarmey, Lynn, Cutcher-Gershenfeld, Joel, Hanson, Brooks, Lehnert, Kerstin, Nosek, Brian, Parsons, Mark, Robinson, Erin, and Wyborn, Lesley

Published
2019
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29. Many Labs 3: Evaluating participant pool quality across the academic semester via replication

Author

Ebersole, Charles R., Atherton, Olivia E., Belanger, Aimee L., Skulborstad, Hayley M., Allen, Jill M., Banks, Jonathan B., Baranski, Erica, Bernstein, Michael J., Bonfiglio, Diane B.V., Boucher, Leanne, Brown, Elizabeth R., Budiman, Nancy I., Cairo, Athena H., Capaldi, Colin A., Chartier, Christopher R., Chung, Joanne M., Cicero, David C., Coleman, Jennifer A., Conway, John G., Davis, William E., Devos, Thierry, Fletcher, Melody M., German, Komi, Grahe, Jon E., Hermann, Anthony D., Hicks, Joshua A., Honeycutt, Nathan, Humphrey, Brandon, Janus, Matthew, Johnson, David J., Joy-Gaba, Jennifer A., Juzeler, Hannah, Keres, Ashley, Kinney, Diana, Kirshenbaum, Jacqeline, Klein, Richard A., Lucas, Richard E., Lustgraaf, Christopher J.N., Martin, Daniel, Menon, Madhavi, Metzger, Mitchell, Moloney, Jaclyn M., Morse, Patrick J., Prislin, Radmila, Razza, Timothy, Re, Daniel E., Rule, Nicholas O., Sacco, Donald F., Sauerberger, Kyle, Shrider, Emily, Shultz, Megan, Siemsen, Courtney, Sobocko, Karin, Weylin Sternglanz, R., Summerville, Amy, Tskhay, Konstantin O., van Allen, Zack, Vaughn, Leigh Ann, Walker, Ryan J., Weinberg, Ashley, Wilson, John Paul, Wirth, James H., Wortman, Jessica, and Nosek, Brian A.

Published
2016
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30. Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015

Author

Camerer, Colin F., Dreber, Anna, Holzmeister, Felix, Ho, Teck-Hua, Huber, Jürgen, Johannesson, Magnus, Kirchler, Michael, Nave, Gideon, Nosek, Brian A., Pfeiffer, Thomas, Altmejd, Adam, Buttrick, Nick, Chan, Taizan, Chen, Yiling, Forsell, Eskil, Gampa, Anup, Heikensten, Emma, Hummer, Lily, Imai, Taisuke, Isaksson, Siri, Manfredi, Dylan, Rose, Julia, Wagenmakers, Eric-Jan, and Wu, Hang

Published
2018
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31. Predicting the replicability of social and behavioural science claims from the COVID-19 Preprint Replication Project with structured expert and novice groups

Author

Marcoci, Alexandru, primary, Wilkinson, David Peter, additional, Abatayo, Anna, additional, Baskin, Ernest, additional, berkman, henk, additional, Buchanan, Erin Michelle, additional, Capitán, Sara, additional, Capitán, Tabaré, additional, Chan, Ginny, additional, Cheng, Kent Jason Go, additional, Coupe, Tom, additional, Dryhurst, Sarah, additional, Duan, Jianhua, additional, Edlund, John, additional, Errington, Timothy M., additional, Fedor, Anna, additional, Fidler, Fiona, additional, Field, James, additional, Fox, Nicholas William, additional, Fraser, Hannah, additional, Freeman, Alexandra L.J., additional, Hanea, Anca, additional, Holzmeister, Felix, additional, Hong, Sanghyun, additional, Huggins, Raquel, additional, Huntington-Klein, Nick, additional, Johannesson, Magnus, additional, Jones, Angela, additional, Kapoor, Hansika, additional, Kerr, John R, additional, Kline Struhl, Melissa, additional, Kolczynska, Marta, additional, Liu, Yang, additional, Loomas, Zachary, additional, Luis, Brianna, additional, Méndez, Esteban, additional, Miske, Olivia, additional, Nast, Carolin, additional, Nosek, Brian A., additional, Parsons, Elan Simon, additional, Pfeiffer, Thomas, additional, Reed, W. Robert, additional, Roozenbeek, Jon, additional, Schlyfestone, Alexa R., additional, Schneider, Claudia R., additional, Soh, Andrew, additional, Tagat, Anirudh, additional, Tutor, Melba, additional, Tyner, Andrew, additional, Urbanska, Karolina, additional, Linden, Sander van der, additional, Vercammen, Ans, additional, and Wintle, Bonnie, additional

Published
2023
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33. Predicting the replicability of social and behavioural science claims from the COVID-19 Preprint Replication Project with structured expert and novice groups

Author

Vercammen, Ans, Reed, W., Linden, Sander van der, Johannesson, Magnus, berkman, henk, Huntington-Klein, Nick, Baskin, Ernest, Capitán, Sara, Urbanska, Karolina, Tagat, Anirudh, Kline Struhl, Melissa, Edlund, John, Holzmeister, Felix, Buchanan, Erin, Tyner, Andrew, Kapoor, Hansika, Huggins, Raquel, Luis, Brianna, Duan, Jianhua, Errington, Timothy, Fidler, Fiona, Pfeiffer, Thomas, Hanea, Anca, Roozenbeek, Jon, Méndez, Esteban, Marcoci, Alexandru, Schneider, Claudia, Kolczynska, Marta, Coupe, Tom, Schlyfestone, Alexa, Nosek, Brian, Liu, Yang, Dryhurst, Sarah, Wintle, Bonnie, Miske, Olivia, Chan, Ginny, Cheng, Kent Jason, Fox, Nicholas, Tutor, Melba, Capitán, Tabaré, Parsons, Elan, Freeman, Alexandra, Hong, Sanghyun, Nast, Carolin, Jones, Angela, Wilkinson, David, Fraser, Hannah, Soh Ph.D., Andrew, Loomas, Zachary, Abatayo, Anna, Kerr, John, Fedor, Anna, and Field, James

Subjects
bepress|Social and Behavioral Sciences|Other Social and Behavioral Sciences, MetaArXiv|Social and Behavioral Sciences, MetaArXiv|Social and Behavioral Sciences|Other Social and Behavioral Sciences, bepress|Social and Behavioral Sciences
Abstract

Replication is an important “credibility control” mechanism for clarifying the reliability of published findings. However, replication is costly, and it is infeasible to replicate everything. Accurate, fast, lower cost alternatives such as eliciting predictions from experts or novices could accelerate credibility assessment and improve allocation of replication resources for important and uncertain findings. We elicited judgments from experts and novices on 100 claims from preprints about an emerging area of research (COVID-19 pandemic) using a new interactive structured elicitation protocol and we conducted 35 new replications. Participants’ average estimates were similar to the observed replication rate of 60%. After interacting with their peers, novices updated both their estimates and confidence in their judgements significantly more than experts and their accuracy improved more between elicitation rounds. Experts’ average accuracy was 0.54 (95% CI: [0.454, 0.628]) after interaction and they correctly classified 55% of claims; novices’ average accuracy was 0.55 (95% CI: [0.455, 0.628]), correctly classifying 61% of claims. The difference in accuracy between experts and novices was not significant and their judgments on the full set of claims were strongly correlated (r=.48). These results are consistent with prior investigations eliciting predictions about the replicability of published findings in established areas of research and suggest that expertise may not be required for credibility assessment of some research findings.

Published
2023

35. Heuristics Used in Reasoning with Multiple Causes and Effects

Author

Ahn, Woo-Kyoung and Nosek, Brian A.

Abstract

Two experiments investigate the conjunction fallacy (judging that conjunctive probabilities are higher than the probabilities of the constituents). The conjunction fallacy was much less for P(E|C) tasks than for P(C|E) tasks. The results are explained in terms of the way people interpret the conditional probabilities. We argue that people prefer to reason from cause to effect (cause-to-effect reasoning heuristic), and for that reason, the instructions given for P(C|E) tasks were misinterpreted, resulting in apparent fallacy. In addition, we provide evidence showing that likelihood judgments are higher with more evidence (more-is-better heuristic).

Published
1998

37. Effects of data availability statements on likelihood of preprint downloads

Author

Errington, Timothy M., Soderberg, Courtney K., and Nosek, Brian A.

Subjects
Social and Behavioral Sciences
Abstract

The purpose of this study is to investigate whether providing preprint readers with information about the public availability of data underlying the results in a preprint alters the perceived trust/credibility of preprints (as measured by download behavior), and whether this depends on the state of the public data availability (publicly available vs. not publicly available)

Published
2023
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39. Conflict of Interest Signal Study

Author

Soderberg, Courtney, Errington, Timothy, and Nosek, Brian

Subjects
FOS: Psychology, Psychology, Social and Behavioral Sciences
Abstract

The purpose of this study is to investigate whether providing preprint readers with information about preprint authors’ conflicts of interest (COIs) alters the perceived trust/credibility of preprints (as measured by download behavior), and whether this depends on the state of the COI (report no conflicts vs. report conflicts)

Published
2022
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40. Public Data Availability Signal Study

Author

Soderberg, Courtney, Errington, Timothy, and Nosek, Brian

Subjects
Social and Behavioral Sciences
Abstract

This is the pre-registration of the final primary analysis strategy that will be used on the unblinded dataset, based on the analysis done on the blinded dataset

Published
2022
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41. Transform to Open Science October Community Panel Summary Report

Author

Gentemann, Chelle, Ivey, Yvonne, Hall, Cynthia, Martinez, Isabella, Murphy, Kevin, Crawford, Steve, Colliander, James, Granados, Monica, Harrison, Dominique, Hsing, Pen-Yuan, Hurt, SherAaron, Kilpatrick, Logan, Nosek, Brian, Perez, Fernando, Sharan, Malvika, and Wu, Qiusheng

Abstract

NASA's Transform to Open Science (TOPS) held a virtual community panel October 5-6, 2022. Each day the team presented TOPS upcoming plans for the Year of Open Science and highlighted emerging trends, success stories, and lessons learned with open science experts.This Panel Summary Report contains a summary of presentations given by TOPS and TOPS partners to the panelists and an overview of panelists’ feedback on strengths, weaknesses, opportunities, and threats regarding the presented information. This feedback will be used to improve TOPS plans for the open science curriculum (OpenCore), community engagement, and overall missions and goals.

Published
2022
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42. Center for Open Science Impact Reports

Author

Riss, Claire, Mellor, David, Pfeiffer, Nicole, Krall, Tina, Grasty, Fielding, Olson, Eric, Steger, Daniel, Staller, Amanda, Elliott, Fitz, Errington, Timothy, Frazier, Matthew, Nosek, Brian, Geiger, Brian, Liu, Yuhuai, Wade, Briana, Shaw, Lisa, Brooks, Ronald, Butler, Blaine, Corell, Doug, Foor, Terry, Tyner, Andrew, Gueguen, Gretchen, Oertelt, Nadja, Wissinger, Whitney, Lowrey, Olivia, Loomas, Zachary, Lynch, Sarah, Hahn, Krystal, Hernandez, Joshua, Markham, Lesley, Pilati, Brian, Rice, Alexis, Robinson, Ashley, Call, Mark, Roma, Doreen, Ikeda, Futa, Walz, Jonathan, Reedy, Marcy, Miske, Olivia, Wang, Huajin, Clark, Matt, Moshontz, Hannah, Booth, Abram, Mawhinney, Brinna, Daley, Macie, Dirzo, Mirka, Chen, Longze, Tordoff, John, and Litherland, David

Published
2022
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43. The Open Scholarship Survey (OSS)

Author

Beaudry, Jennifer, Chen, Donna, Cook, Bryan, Errington, Timothy, Fortunato, Laura, Given, Lisa, Hahn, Krystal, Ihle, Malika, Mellor, David, Nosek, Brian, Pfeiffer, Nicole, Reedy, Marcy, Soderberg, Courtney, Tyner, Andrew, Dirzo, Mirka, Markham, Lesley, and Wang, Huajin

Subjects
open access, replication, incentives, data sharing, code sharing, robustness, reproduction, open science practices, preregistration, open science, preprints, open science attitudes, materials sharing, null results
Abstract

The OSS is a standard, modular survey to assess open scholarship attitudes, perceptions, and behavior of researchers

Published
2022
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47. Transcripts from 2022 October TOPS Community Panel

Author

Gentemann, Chelle, Ivey, Yvonne, Martinez, Isabella, Hall, Cynthia, Murphy, Kevin, Hanson, Brooks, Lyon, Laura, Vrouwenvelder, Kristina, Colliander, James, Granados, Monica, Hsing, Pen-Yuan, SherAaron Hurt, Nosek, Brian, Perez, Fernando, Sharan, Malvika, Wu, Quisheng, Kilpatrick, Logan, and Groenen, Danielle

Subjects
open science, nasa
Abstract

Transcripts for the TOPS 2022 October Community Panel.&nbsp

Published
2022
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48. Investigating variation in replicability: A 'Many Labs' Replication Project

Author

Klein, Richard, Ratliff, Kate, Nosek, Brian, Vianello, Michelangelo, Pilati, Ronaldo, Cemalcilar, Zeynep, Chandler, Jesse, Devos, Thierry, Galliani, Elisa, Brandt, Mark, van 't Veer, Anna, Levitan, Carmel, Kurtz, Jaime, Joy-Gaba, Jennifer, Ehrlinger, Joyce, Bernstein, Michael, Morris, Wendy, Vaughn, Leigh Ann, Wichman, Aaron, Rutchick, Abraham, Kappes, Heather, Brumbaugh, Claudia, Nelson, Anthony, Eisner, Matthew, Smith, Robert, Woodzicka, Julie, Bocian, Konrad, Frankowska, Natalia, Schmidt, Kathleen, Skorinko, Jeanine, Storbeck, Justin, Thompson, Donna, Packard, Grant, van Swol, Lyn, Nier, Jason, Cheong, Winnee, Davis, William, Mallett, Robyn, Huntsinger, Jeffrey, Bahník, Štěpán, Vranka, Marek, Hasselman, Fred, IJzerman, Hans, and Krueger, Lacy

Subjects
replication, psychology
Abstract

We will attempt to replicate 12 effects in a single experimental package across numerous labs. Variations between lab conditions and sample characteristics will be analyzed to investigate how these factors might influence replication success.

Published
2022
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50. Native American IAT 2004-2017

Author

Xu, Kaiyuan, Lofaro, Nicole, Nosek, Brian, and Greenwald, Anthony

Subjects
Stimuli, Web study, Data, Project Implicit, iat, Native American, Experiment material, White, Codebook, Native American IAT, European American, Native
Published
2022
Full Text
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