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<tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1177/1474704918802412'></a>
<div class='mdl-card__supporting-text'><div class='fulltextcomponent'><div class='impact-info'><span style='margin-left:7px;' title='Article PDF (postprint) has been downloaded 1601 times (as of February 16, 2019)'>
<i class='fas fa-download'></i> 1.6K </span></div> <a href='https://journals.sagepub.com/doi/pdf/10.1177/1474704918802412' target='_blank' class='black' title='View PDF of this article (postprint).'>
<img src='logos/author-logos/sprite-icons/pdf.png' class='pdf-icon transparent full-text'></a> <br><div class='impact-info'></div> <span class='label label-info-html full-text'><a href='https://journals.sagepub.com/doi/full/10.1177/1474704918802412' target='_blank'
class='black' title='View HTML version of this article (postprint).'>HTML</a></span> </div><div class='article-type-line'>
<span class='label label-info-pecan'
title='Article reports a (traditional) meta-analysis of a target effect/phenomenon'>Reanalysis - Meta-analysis</span>
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<a href='#10.1177/1474704918802412'><i class='fas fa-link link-button'></i></a>
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<div class='article-title'>Meta-analysis of the effect of red on perceived attractiveness</div>
<div class='author-text'>GK Lehmann, AJ Elliot, & RJ Calin-Jageman (2018)</div>
<div class='journal-text'>Evolutionary Psychology</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1177/1474704918802412' target='_blank' class='doi-dimmed grey'>10.1177/1474704918802412</a></div><br><div class='transparency-line'><a title='Preregistration information is not available'><img src='logos/author-logos/sprite-icons/preregistered-unavailable.png'
class='shrunk-20'></a><div style='display:inline;' class='popUpOnHover'>
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<div class='abstractText minimize'>We conducted meta-analyses of studies that test the red-romance hypothesis, which is that the color red enhances heterosexual attraction in romantic contexts. For men rating women, we found a small, statistically significant effect (d = 0.26 [0.12, 0.40], p = .0004, N= 2,961), with substantial heterogeneity, Q(44) = 172.5, pQ < .0001, I2 = 89% [82, 94], and equivocal results regarding the possibility of upward bias in the estimate. For women rating men, we found a very small effect (d = 0.13 [0.01, 0.25], p = .03, N = 2,739), with substantial heterogeneity, Q(35) = 73.0, pQ = .0002, I2 = 53% [33, 80], and evidence of upward bias in the estimate. Moderator analyses suggest effect sizes may have declined over time (both genders), may be largest when an original shade of red is used (men only), and may be smaller in preregistered studies (women only). We present contrasting interpretations and suggestions for future research.</div><div class='key-words'> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>attraction</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>color</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>mate selection</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>red</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>systematic review</span></span></div>
<p class="imglist">
<a href="logos/author-logos/figures/lec2018-figure-6.png" data-fancybox="images" data-caption="Lehmann, Elliot, & Calin-Jageman (2018)- Figure 6">
<img src="logos/author-logos/figures/lec2018-figure-6.png" width="85px" height="85px;" style="object-fit:cover;"/>
</a>
<a href="logos/author-logos/figures/lec2018-figure-7.png" data-fancybox="images" data-caption="Lehmann, Elliot, & Calin-Jageman (2018)- Figure 7">
<img src="logos/author-logos/figures/lec2018-figure-7.png" width="85px" height="85px;" style="object-fit:cover;"/>
</a>
</p>
<div class='secondary-section'>
<div class='secondary-section-on-hover'>
<div class='author-contributions minimizeAC'></div>
<div class='competing-interests-info'><strong title='Competing commercial or financial interests.'>Competing interests</strong>: None to declare.</div>
<div class='funding-sources-info'><strong>Funding sources</strong>: The author(s) received no financial support for the research, authorship, and/or publication of this article.</div>
<div class='peer-review-info'></div>
</div>
</div>
</div> <div class='addition-date-text'>Added: February 16, 2019</div>
</div></div>
</td><td></td><td></td><td></td><td>od</td><td>rc</td><td>reanalysis - meta-analysis</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1177/0956797617723726'></a>
<div class='mdl-card__supporting-text'><div class='fulltextcomponent'><div class='impact-info'><span style='margin-left:7px;' title='Article PDF (postprint) has been downloaded 1907 times (as of January 24, 2019)'>
<i class='fas fa-download'></i> 1.9K </span><span style='margin-left:7px;' title='Article has been cited 5 times (as of January 24, 2019; Google Scholar)'>
<i class='fas fa-quote-right'></i> 5 </span></div> <a href='http://journals.sagepub.com.sci-hub.tw/doi/metrics/10.1177/0956797617723726' target='_blank' class='black' title='View PDF of this article (postprint).'>
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<div class='article-title'>Probing birth-order effects on narrow traits using specification-curve analysis</div>
<div class='author-text'>JM Rohrer, B Egloff, SC Schmukle (2017)</div>
<div class='journal-text'>Psychological Science</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1177/0956797617723726' target='_blank' class='doi-dimmed grey'>10.1177/0956797617723726</a></div><br><div class='transparency-line'><a title='Preregistration information is not available'><img src='logos/author-logos/sprite-icons/preregistered-unavailable.png'
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<div class='abstractText minimize'>The idea that birth-order position has a lasting impact on personality has been discussed for the past 100 years. Recent large-scale studies have indicated that birth-order effects on the Big Five personality traits are negligible. In the current study, we examined a variety of more narrow personality traits in a large representative sample (n = 6,500–10,500 in between-family analyses; n = 900–1,200 in within-family analyses). We used specification-curve analysis to assess evidence for birth-order effects across a range of models implementing defensible yet arbitrary analytical decisions (e.g., whether to control for age effects or to exclude participants on the basis of sibling spacing). Although specification-curve analysis clearly confirmed the previously reported birth-order effect on intellect, we found no meaningful effects on life satisfaction, locus of control, interpersonal trust, reciprocity, risk taking, patience, impulsivity, or political orientation. The lack of meaningful birth-order effects on self-reports of personality was not limited to broad traits but also held for more narrowly defined characteristics.</div><div class='key-words'> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>birth-order effects</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>siblings</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>trust</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>risk taking</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>reciprocity</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>political attitudes</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>specification-curve analysis</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>open materials</span></span></div><div class='secondary-section'>
<div class='secondary-section-on-hover'>
<div class='author-contributions minimizeAC'>All the authors developed the study concept. J. M. Rohrer performed the data analysis under the supervision of S. C. Schmukle. J. M. Rohrer drafted the manuscript, and all the authors provided critical revisions. All the authors approved the final version of the manuscript for submission.</div>
<div class='competing-interests-info'><strong title='Competing commercial or financial interests.'>Competing interests</strong>: None to declare.</div>
<div class='funding-sources-info'></div>
<div class='peer-review-info'><strong>Editor</strong>: <span style='color:#009933;'>BW Roberts</span></div>
</div>
</div>
</div> <div class='addition-date-text'>Added: February 10, 2019</div>
</div></div>
</td><td></td><td></td><td></td><td>od</td><td>rc</td><td>reanalysis - robustness</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1525/collabra.24'></a>
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<div class='article-title'>Initial evidence that individuals form new relationships with partners that more closely match their ideal preferences</div>
<div class='author-text'>L Campbell, K Chin, & SCE Stanton (2016)</div>
<div class='journal-text'>Collabra</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1525/collabra.24' target='_blank' class='doi-dimmed grey'>10.1525/collabra.24</a></div><br><div class='transparency-line'><a title='Preregistration information is not available'><img src='logos/author-logos/sprite-icons/preregistered-unavailable.png'
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<div class='abstractText minimize'>An important assumption in interpersonal attraction research asking participants about their ideal partner preferences is that these preferences play a role in actual mate choice and relationship formation. Existing research investigating the possible predictive validity of ideal partner preference, however, is limited by the fact that none of it has focused on the actual process of relationship formation. The current research recruited participants when single, assessed ideal partner preferences across 38 traits and attributes, tracked participants’ relationship status over 5 months, and successfully recruited the new partners of 38 original participants to assess their self-evaluations across the same 38 traits and attributes. Using multilevel modeling to assess the correspondence between ideal partner preferences and self-evaluations within couple, the results showed a positive within-couple association that was not accounted for by personality similarity or stereotype accuracy. We discuss these results with respect to the current literature on the predictive validity of ideal partner preferences in relationship formation. </div><div class='key-words'> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>ideal partner preferences</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>close relationships</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>relationship formation</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>attraction</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>multilevel modeling</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>longitudinal</span></span></div><div class='secondary-section'>
<div class='secondary-section-on-hover'>
<div class='author-contributions minimizeAC'></div>
<div class='competing-interests-info'><strong title='Competing commercial or financial interests.'>Competing interests</strong>: None to declare.</div>
<div class='funding-sources-info'><strong>Funding sources</strong>: This research was supported by a grant awarded to Lorne Campbell from the Social Sciences and Humanities Research Council (SSHRC) of Canada.</div>
<div class='peer-review-info'><strong>Editor</strong>: <span style='color:#009933;'>S Gosling</span> <strong>Reviewers</strong>: <span style='color:#009933;'>P Eastwick; Anonymous reviewer 2</span><div class='open-peer-review'>
<a href='http://s3-eu-west-1.amazonaws.com/ubiquity-partner-network/ucp/journal/collabra/PR-Collabra-24.pdf' target='_blank'><i class='fas fa-link'></i> Open peer review <i class='fas fa-external-link-alt'></i></a>
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</div>
</div>
</div> <div class='addition-date-text'>Added: February 5, 2019</div>
</div></div>
</td><td></td><td>om</td><td></td><td>od</td><td>rc</td><td>original</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1177/2515245917745629'></a>
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<i class='fas fa-download'></i> 13.2K </span><span style='margin-left:7px;' title='Article has been cited 13 times (as of January 25, 2019; Google Scholar)'>
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<div class='article-title'>Thinking clearly about correlations and causation: Graphical causal models for observational data</div>
<div class='author-text'>JM Rohrer (2018)</div>
<div class='journal-text'>Advances in Methods and Practices in Psychological Science</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1177/2515245917745629' target='_blank' class='doi-dimmed grey'>10.1177/2515245917745629</a></div><div class='more-button full-text' id='moreDiv-10.1177/2515245917745629' style='margin-top:4px;'>
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<div class='abstractText minimize'>Correlation does not imply causation; but often, observational data are the only option, even though the research question at hand involves causality. This article discusses causal inference based on observational data, introducing readers to graphical causal models that can provide a powerful tool for thinking more clearly about the interrelations between variables. Topics covered include the rationale behind the statistical control of third variables, common procedures for statistical control, and what can go wrong during their implementation. Certain types of third variables—colliders and mediators—should not be controlled for because that can actually move the estimate of an association away from the value of the causal effect of interest. More subtle variations of such harmful control include using unrepresentative samples, which can undermine the validity of causal conclusions, and statistically controlling for mediators. Drawing valid causal inferences on the basis of observational data is not a mechanistic procedure but rather always depends on assumptions that require domain knowledge and that can be more or less plausible. However, this caveat holds not only for research based on observational data, but for all empirical research endeavors.</div><div class='key-words'> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>directed acyclic graphs</span></span></div><div class='secondary-section'>
<div class='secondary-section-on-hover'>
<div class='author-contributions minimizeAC'></div>
<div class='competing-interests-info'><strong title='Competing commercial or financial interests.'>Competing interests</strong>: None to declare.</div>
<div class='funding-sources-info'></div>
<div class='peer-review-info'><strong>Editor</strong>: <span style='color:#009933;'>DJ Simons</span></div>
</div>
</div>
</div> <div class='addition-date-text'>Added: February 4, 2019</div>
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</td><td></td><td></td><td></td><td></td><td></td><td>conceptual</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1177/2515245918797607'></a>
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<i class='fas fa-quote-right'></i> 11 </span></div> <a href='https://ppw.kuleuven.be/okp/_pdf/Moshontz2018TPSAA.pdf' target='_blank' class='black' title='View PDF of this article (postprint).'>
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<div class='article-title'>The psychological science accelerator: Advancing psychology through a distributed collaborative network</div>
<div class='author-text'>H Moshontz, L Campbell, CR Ebersole, H IJzerman, HL Urry, ..., & PS Forscher (2018)</div>
<div class='journal-text'>Advances in Methods and Practices in Psychological Science</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1177/2515245918797607' target='_blank' class='doi-dimmed grey'>10.1177/2515245918797607</a></div><div class='more-button full-text' id='moreDiv-10.1177/2515245918797607' style='margin-top:4px;'>
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<div class='abstractText minimize'>Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions or replicate prior research in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time limited), efficient (in that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.</div><div class='key-words'> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>Psychological Science Accelerator</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>crowdsourcing</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>generalizability</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>theory development</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>large-scale collaboration</span></span></div><div class='secondary-section'>
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<div class='author-contributions minimizeAC'>Authors are listed in tiers according to their contributions. Within tiers, authors are listed in alphabetical order. H. Moshontz and C. R. Chartier oversaw the preparation of the original draft of the manuscript and its subsequent review and editing. Authors in the first tier (H. Moshontz through H. L. Urry) were central to drafting, reviewing, and editing the manuscript. Authors in the second tier (P. S. Forscher through E. D. Musser) contributed substantially to drafting, reviewing, and editing the manuscript. Authors in the third tier (J. Antfolk through J. Protzko) contributed to specific sections of the original draft of the manuscript and provided reviewing and editing. Authors in the fourth tier (B. Aczel through J. H. Zickfeld) contributed to reviewing and editing the manuscript. Authors in the fifth tier (J. D. Arnal through M. A. Silan) contributed to conceptualization of the project by drafting policy and procedural documents upon which the manuscript is built, and also helped review and edit the manuscript. G. Pfuhl created Figure 1, and J. Olsen created Figure 2. C. R. Chartier initiated the project and oversees all activities of the Psychological Science Accelerator.</div>
<div class='competing-interests-info'><strong title='Competing commercial or financial interests.'>Competing interests</strong>: None to declare.</div>
<div class='funding-sources-info minimizeFunding'>H. IJzerman’s research is partly supported by the French National Research Agency in the framework of the “Investissements d’avenir” program (ANR-15-IDEX-02). E. D. Musser’s work is supported in part by the U.S. National Institute of Mental Health (Grant R03MH110812-02). S. Fiedler’s work is supported in part by the Gielen-Leyendecker Foundation. D. A. Forero is supported by research grants from Colciencias and Vicerrectoría de Ciencia, Tecnología e Innovación. This material is based on work that has been supported by the National Science Foundation Graduate Research Fellowship awarded to N. A. Coles and by a National Science Foundation grant (DGE-1445197) to S. M. Garrison. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. T. Gill’s work is partially supported by the Canada Research Chairs Program (Social Sciences and Humanities Research Council of Canada). M. A. Vadillo’s work is supported by Comunidad de Madrid (Programa de Atracción de Talento Investigador, Grant 2016-T1/SOC-1395). E. Vergauwe’s work is supported in part by the Swiss National Science Foundation (Grant PZ00P1_154911). L. M. DeBruine’s work is partially supported by the European Research Council (Grant 647910, KINSHIP). A. M. Fernandez’s work is partially supported by Fondecyt (Grant 1181114). P. M. Isager’s work is partially supported by the Netherlands Organisation for Scientific Research (VIDI Grant 452-17-013).</div>
<div class='peer-review-info'><strong>Editor</strong>: <span style='color:#009933;'>DJ Simons</span></div>
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<div class='article-title'>Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs</div>
<div class='author-text'>D Lakens (2013)</div>
<div class='journal-text'>Frontiers in Psychology</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.3389/fpsyg.2013.00863' target='_blank' class='doi-dimmed grey'>10.3389/fpsyg.2013.00863</a></div><br><div class='transparency-line'><div style='display:inline;' class='popUpOnHover'>
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<div class='abstractText minimize'>Effect sizes are the most important outcome of empirical studies. Most articles on effect sizes highlight their importance to communicate the practical significance of results. For scientists themselves, effect sizes are most useful because they facilitate cumulative science. Effect sizes can be used to determine the sample size for follow-up studies, or examining effects across studies. This article aims to provide a practical primer on how to calculate and report effect sizes for t-tests and ANOVA’s such that effect sizes can be used in a-priori power analyses and meta-analyses. Whereas many articles about effect sizes focus on between-subjects designs and address within-subjects designs only briefly, I provide a detailed overview of the similarities and differences between within- and between-subjects designs. I suggest that some research questions in experimental psychology examine inherently intra-individual effects, which makes effect sizes that incorporate the correlation between measures the best summary of the results. Finally, a supplementary spreadsheet is provided to make it as easy as possible for researchers to incorporate effect size calculations into their workflow.</div><div class='key-words'> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>effect sizes</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>power analysis</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>cohen's d</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>eta-squared</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>sample size planning</span></span></div><div class='secondary-section'>
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<div class='competing-interests-info'><strong title='Competing commercial or financial interests.'>Competing interests</strong>: None to declare.</div>
<div class='funding-sources-info'><strong>Funding sources</strong>: None to declare.</div>
<div class='peer-review-info'><strong>Editor</strong>: <span style='color:#009933;'>B Hommel</span> <strong>Reviewers</strong>: <span style='color:#009933;'>M Bakker; B Bocanegra</span></div>
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<span class='label label-info-brown'>Replication <span class='badge badge-repnum'>1609</span></span>
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<span style='font-size:12px;'>Article reports 1609 replications of 28 social/cognitive psychology effects</span>
<br><br>
<span style='font-size:10px;color:gray;'>A replication is a study that uses a methodology that is 'close' or 'very close'
to a previous study (see <a href='http://curatescience.org/logos/replication-taxonomy-v4_small.png' target='_blank'>replication taxonomy</a> for details).
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<div class='article-title'>Many Labs 2: Investigating variation in replicability across samples and settings</div>
<div class='author-text'>RA Klein, ..., D Lakens, ... , & BA Nosek (2018)</div>
<div class='journal-text'>Advances in Methods and Practices in Psychological Science</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1177/2515245918810225' target='_blank' class='doi-dimmed grey'>10.1177/2515245918810225</a></div><br><div class='transparency-line'><div style='display:inline;' class='popUpOnHover'>
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<a href='https://www.psychologicalscience.org/publications/psychological_science/ps-submissions#DISC' target='_blank'>
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<li><strong>Excluded data (subjects/observations):</strong> Full details reported in article.</li>
<li><strong>Experimental conditions:</strong> Full details reported in article.</li>
<li><strong>Outcome measures:</strong> Full details reported in article.</li>
<li><strong>Sample size determination:</strong> Full details reported in article.</li>
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<div class='abstractText minimize'>We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen’s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.</div><div class='key-words'> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>social psychology</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>cognitive psychology</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>replication</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>culture</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>individual differences</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>sampling effects</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>situational effects</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>meta-analysis</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>Registered Report</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>open data</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>open materials</span></span> <span class='mdl-chip small-chip'>
<span class='mdl-chip__text small-chip-text'>preregistered</span></span></div>
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<div class='author-contributions minimizeAC'>F. Hasselman, R. A. Klein, B. A. Nosek, and M. Vianello coordinated the project. Š. Bahník, J. Chandler, K. S. Corker, F. Hasselman, H. IJzerman, R. A. Klein, B. A. Nosek, K. Schmidt, M. A. L. M. van Assen, L. A.Vaughn, M. Vianello, and A. L. Wichman designed the study. J. R. Axt, Š. Bahník, M. A. Conway, P. G. Curran, R. A. Klein, N. P. Lipsey, J. E. Losee, G. Pogge, and K. Schmidt developed the materials. J. R. Axt, Š. Bahník, M. Berkics, J. Chandler, E. E. Chen, S. Coen, M. A. Conway, K. S. Corker, W. E. Davis, T. Gnambs, F. Hasselman, H. IJzerman, R. A. Klein, C. A. Levitan, W. L. Morris, B. A. Nosek, K. Schmidt, V. Smith-Castro, J. Stouten, M. A. L. M. van Assen, L. A. Vaughn, M. Vianello, and A. L. Wichman wrote the proposal for the project. The data were collected by B. G. Adams, R. B. Adams, Jr., S. Alper, M. Aveyard, M. T. Babalola, Š. Bahník, R. Batra, M. Berkics, M. J. Bernstein, D. R. Berry, O. Bialobrzeska, E. D. Binan, K. Bocian, M. J. Brandt, R. Busching, A. Cabak Rédei, H. Cai, F. Cambier, K. Cantarero, C. L. Carmichael, F. Ceric, J. Chandler, J.-H. Chang, A. Chatard, E. E. Chen, W. Cheong, D. C. Cicero, S. Coen, J. A. Coleman, B. Collisson, K. S. Corker, P. G. Curran, F. Cushman, Z. K. Dagona, I. Dalgar, A. Dalla Rosa, W. E. Davis, M. de Bruijn, L. De Schutter, T. Devos, M. de Vries, C. Doğulu, N. Dozo, K. N. Dukes, Y. Dunham, K. Durrheim, C. R. Ebersole, J. E. Edlund, A. Eller, A. S. English, C. Finck, N. Frankowska, M.-Á. Freyre, M. Friedman, E. M. Galliani, J. C. Gandi, T. Ghoshal, S. R. Giessner, T. Gill, T. Gnambs, Á. Gómez, R. González, J. Graham, J. E. Grahe, I. Grahek, E. G. T. Green, K. Hai, M. Haigh, E. L. Haines, M. P. Hall, F. Hasselman, M. E. Heffernan, J. A. Hicks, P. Houdek, J. R. Huntsinger, H. P. Huynh, Hans IJzerman, Y. Inbar, Å. H. Innes-Ker, W. Jiménez-Leal, M.-S. John, J. A. Joy-Gaba, R. G. Kamiloğlu, H. B. Kappes, S. Karabati, H. Karick, V. N. Keller, A. Kende, N. Kervyn, R. A. Klein, G. Knežević, C. Kovacs, L. E. Krueger, G. Kurapov, J. Kurtz, D. Lakens, L. B. Lazarević, C. A. Levitan, N. A. Lewis, Jr., S. Lins, E. Maassen, A. T. Maitner, W. Malingumu, R. K. Mallett, S. A. Marotta, J. Međedović, F. Mena-Pacheco, T. L. Milfont, W. L. Morris, S. C. Murphy, A. Myachykov, N. Neave, K. Neijenhuijs, A. J. Nelson, F. Neto, A. L. Nichols, A. Ocampo, S. L. O’Donnell, H. Oikawa, M. Oikawa, E. Ong, G. Orosz, M. Osowiecka, G. Packard, R. Pérez-Sánchez, B. Petrović, R. Pilati, B. Pinter, L. Podesta, M. M. H. Pollmann, A. M. Rutchick, P. Saavedra, A. K. Saeri, E. Salomon, F. D. Schönbrodt, M. B. Sekerdej, D. Sirlopú, J. L. M. Skorinko, M. A. Smith, V. Smith-Castro, K. C. H. J. Smolders, A. Sobkow, W. Sowden, P. Spachtholz, M. Srivastava, T. G. Steiner, J. Stouten, C. N. H. Street, O. K. Sundfelt, S. Szeto, E. Szumowska, A. C. W. Tang, N. Tanzer, M. J. Tear, J. Theriault, M. Thomae, D. Torres, J. Traczyk, J. M. Tybur, A. Ujhelyi, R. C. M. van Aert, M. A. L. M. van Assen, M. van der Hulst, P. A. M. van Lange, A. E. van ’t Veer, A. Vásquez-Echeverría, L. A. Vaughn, A. Vázquez, L. D. Vega, C. Verniers, M. Verschoor, I. P. J. Voermans, M. A. Vranka, C. Welch, A. L. Wichman, L. A. Williams, M. Wood, J. A. Woodzicka, M. K. Wronska, L. Young, J. M. Zelenski, and Z. Zhijia. F. Hasselman, M. Vianello, and R. A. Klein analyzed the data, with support from K. S. Corker, B. A. Nosek, R. C. M. van Aert, and M. A. L. M. van Assen. F. Hasselman and B. A. Nosek designed the figures. R. A. Klein, B. A. Nosek, and M. Vianello wrote the report. All the authors commented on, edited, and approved the submitted manuscript.</div>
<div class='competing-interests-info'><strong title='Competing commercial or financial interests.'>Competing interests</strong>: Brian A. Nosek is Executive Director of the nonprofit Center for Open Science, which has a mission to increase openness, integrity, and reproducibility of research.</div>
<div class='funding-sources-info minimizeFunding'>This research was supported by the Center for Open Science and by a grant through the Association for Psychological Science from the Laura and John Arnold Foundation. The research in Chile was supported by Fondap Grant 15130009 from the Center for Social Conflict and Cohesion Studies.</div>
<div class='peer-review-info'><strong>Editor</strong>: <span style='color:#009933;'>DJ Simons</span></div>
</div>
</div>
</div> <div class='addition-date-text'>Added: November 20, 2018</div>
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</td><td>rs</td><td>om</td><td>preregplus</td><td>od</td><td>rc</td><td>replication</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1525/collabra.181'></a>
<div class='mdl-card__supporting-text'><div class='fulltextcomponent'><div class='impact-info'></div> <a href='https://www.collabra.org/articles/10.1525/collabra.181/galley/215/' target='_blank' class='black' title='View PDF of this article (postprint).'>
<img src='logos/author-logos/sprite-icons/pdf.png' class='pdf-icon transparent full-text'></a> <br><div class='impact-info'></div> <span class='label label-info-html full-text'><a href='https://www.collabra.org/article/10.1525/collabra.181/' target='_blank'
class='black' title='View HTML version of this article (postprint).'>HTML</a></span> <br><div class='impact-info'></div> <span class='label label-info-purple full-text'><a href='https://psyarxiv.com/vu8je/' target='_blank'
class='black' title='View preprint of this article.'><i class='ai ai-osf ai-2x small-icon'></i> Preprint</a></span></div><div class='article-type-line'>
<div style='display:inline;' class='popUpOnHover'>
<span class='label label-info-brown'>Replication <span class='badge badge-repnum'>8</span></span>
<span class='toDisplayRepDetails popUpStyle'>
<span style='font-size:12px;'>Article reports 8 replications of 8 word segmentation effects</span>
<br><br>
<span style='font-size:10px;color:gray;'>A replication is a study that uses a methodology that is 'close' or 'very close'
to a previous study (see <a href='http://curatescience.org/logos/replication-taxonomy-v4_small.png' target='_blank'>replication taxonomy</a> for details).
</span></span></div>
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<div class='article-title'>The meta-science of adult statistical word segmentation: Part 1</div>
<div class='author-text'>Huartshorne, Skorb, Dietz, Garcia et al. (2019)</div>
<div class='journal-text'>Collabra</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1525/collabra.181' target='_blank' class='doi-dimmed grey'>10.1525/collabra.181</a></div><br><div class='transparency-line'><div style='display:inline;' class='popUpOnHover'>
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<span class='transp-popup-main-heading'>Preregistered protocol</span>
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<a href='https://osf.io/vh6b9/' target='_blank'> <i class='fas fa-link'></i> <i class='ai ai-osf ai-2x small-icon'></i> <i class='fas fa-external-link-alt'></i></a>
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<div class='abstractText minimize'>We report the first set of results in a multi-year project to assess the robustness – and the factors promoting robustness – of the adult statistical word segmentation literature. This includes eight total experiments replicating six different experiments. The purpose of these replications is to assess the reproducibility of reported experiments, examine the replicability of their results, and provide more accurate effect size estimates. Reproducibility was mixed, with several papers either lacking crucial details or containing errors in the description of method, making it difficult to ascertain what was done. Replicability was also mixed: although in every instance we confirmed above-chance statistical word segmentation, many theoretically important moderations of that learning failed to replicate. Moreover, learning success was generally much lower than in the original studies. In the General Discussion, we consider whether these differences are due to differences in subject populations, low power in the original studies, or some combination of these and other factors. We also consider whether these findings are likely to generalize to the broader statistical word segmentation literature.</div>
<p class="imglist">
<a href="logos/author-logos/figures/hsdg2019-figure-4.png" data-fancybox="images" data-caption="Huartshorne, Skorb et al. (2019) - Figure 4">
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<a href="logos/author-logos/figures/hsdg2019-table-3.png" data-fancybox="images" data-caption="Huartshorne, Skorb et al. (2019) - Table 3">
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</div> <div class='addition-date-text'>Added: October 25, 2018</div>
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</td><td></td><td>om</td><td>preregplus</td><td>od</td><td>rc</td><td>replication</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1002/per.2145'></a>
<div class='mdl-card__supporting-text'><div class='fulltextcomponent'><div class='impact-info'></div> <a href='http://onlinelibrary.wiley.com.sci-hub.tw/doi/pdf/10.1002/per.2145' target='_blank' class='black' title='View PDF of this article (postprint).'>
<img src='logos/author-logos/sprite-icons/pdf.png' class='pdf-icon transparent full-text'></a> <br><div class='impact-info'></div> <span class='label label-info-purple full-text'><a href='https://osf.io/fwzus/' target='_blank'
class='black' title='View preprint of this article.'><i class='ai ai-osf ai-2x small-icon'></i> Preprint</a></span></div><div class='article-type-line'>
<span class='label label-info-black'
title='Article reports original empirical observations (not directly comparable to previous research'>Original</span>
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<a href='#10.1002/per.2145'><i class='fas fa-link link-button'></i></a>
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<div class='article-title'>From motive dispositions to states to outcomes: An intensive experience sampling study on communal motivational dynamics in couples</div>
<div class='author-text'>Zygar, Hagemeyer, Pusch, & Schönbrodt (2018)</div>
<div class='journal-text'>European Journal of Personality</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1002/per.2145' target='_blank' class='doi-dimmed grey'>10.1002/per.2145</a></div><br><div class='transparency-line'><div style='display:inline;' class='popUpOnHover'>
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<span class='transp-popup-main-heading'>Reporting Standards</span><br>
<span style='font-size:10px;font-weight:600;color:gray;'>Study complies with the
<a href='https://www.psychologicalscience.org/publications/psychological_science/ps-submissions#DISC' target='_blank'>
Basic 4 (at submission)</a> <img src='logos/author-logos/sprite-icons/disclosure-available.png' class='shrunk-16 transparent'> reporting standard:</span>
<ol>
<li><strong>Excluded data (subjects/observations):</strong> Full details reported in article.</li>
<li><strong>Experimental conditions:</strong> Full details reported in article.</li>
<li><strong>Outcome measures:</strong> Full details reported in article.</li>
<li><strong>Sample size determination:</strong> Full details reported in article.</li>
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</div><div id='abstract-section-10.1002/per.2145' class='abstract-section' style='display:none;'>
<div class='abstractText minimize'>Embedded in a theoretically founded process model (termed Dynamics of Motive Satisfaction, ‘DynaMoS’), the present study examined the links between the implicit dispositional communion motive, everyday motivational dynamics, and relationship outcomes in couples. Within‐subject processes are proposed to explain between‐subject associations of dispositional motives and relationship satisfaction. For an empirical test of the model, data on the dispositional partner‐related need for communion and global relationship satisfaction were obtained from 152 individuals in heterosexual relationships. In an extensive experience sampling spanning 2 weeks, a subsample of 130 individuals answered questions about their current motivational states, mood, state relationship satisfaction, and experiences with their partner five times a day. The results were largely consistent with the DynaMoS model: (1) individuals with a strong dispositional implicit communion motive reported more often to be in a communal motivational state; (2) communally motivated individuals were more likely to engage in subsequent instrumental behaviour; and (3) relationship experiences that potentially satisfy communion motivation led to more positive relationship outcomes when individuals were motivated before compared with when they were not. It is discussed how these results and the experience sampling method can foster our understanding of how dispositional characteristics translate into everyday processes and shape relationship outcomes.</div><div class='secondary-section'>
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</div> <div class='addition-date-text'>Added: August 1, 2018</div>
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</td><td>rs</td><td>om</td><td>preregplus</td><td>od</td><td>rc</td><td>original</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1177/2515245918773742'></a>
<div class='mdl-card__supporting-text'><div class='fulltextcomponent'><div class='impact-info'></div> <a href='http://sci-hub.tw/http://journals.sagepub.com/doi/abs/10.1177/2515245918773742' target='_blank' class='black' title='View PDF of this article (postprint).'>
<img src='logos/author-logos/sprite-icons/pdf.png' class='pdf-icon transparent full-text'></a> <br><div class='impact-info'></div> <span class='label label-info-purple full-text'><a href='https://psyarxiv.com/zqkyt' target='_blank'
class='black' title='View preprint of this article.'><i class='ai ai-osf ai-2x small-icon'></i> Preprint</a></span></div><div class='article-type-line'>
<span class='label label-info-pecan'
title='Article reports a reanalysis of results from previously published studies (meta-research).'>Reanalysis - Meta-research</span>
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<a href='#10.1177/2515245918773742'><i class='fas fa-link link-button'></i></a>
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<div class='article-title'>Quantifying support for the null hypothesis in psychology: An empirical investigation</div>
<div class='author-text'>Aczel, Palfi, Szollosi, Kovacs, ..., & Wagenmakers (2018)</div>
<div class='journal-text'>Advances in Methods and Practices in Psychological Science</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1177/2515245918773742' target='_blank' class='doi-dimmed grey'>10.1177/2515245918773742</a></div><br><div class='transparency-line'><div style='display:inline;' class='popUpOnHover'>
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<div class='abstractText minimize'>In the traditional statistical framework, nonsignificant results leave researchers in a state of suspended disbelief. This study examines, empirically, the treatment and evidential impact of nonsignificant results. Our specific goals were twofold: to explore how psychologists interpret and communicate nonsignificant results, and to assess how much these results constitute evidence in favor of the null hypothesis. Firstly, we examined all nonsignificant findings mentioned in the abstracts of the 2015 volume of Psychonomic Bulletin & Review, Journal of Experimental Psychology: General, and Psychological Science (N = 137). In 72% of cases, nonsignificant results were misinterpreted, in the sense that authors inferred that the effect was absent. Secondly, a Bayes factor reanalysis revealed that fewer than 5% of the nonsignificant findings provided strong evidence (i.e., BF01 > 10) in favor of the null hypothesis compared to the alternative hypothesis. We recommend that researchers expand their statistical toolkit in order to correctly interpret nonsignificant results and to be able to evaluate the evidence for and against the null hypothesis.</div><div class='secondary-section'>
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</div> <div class='addition-date-text'>Added: July 20, 2018</div>
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</td><td></td><td></td><td>preregplus</td><td>od</td><td>rc</td><td>reanalysis - meta-research</td></tr><tr><td><div class='demo-card-wide mdl-card mdl-shadow--2dp'> <a class='anchor' id='10.1016/j.cortex.2016.03.019'></a>
<div class='mdl-card__supporting-text'><div class='fulltextcomponent'><div class='impact-info'></div> <a href='http://sci-hub.tw/10.1016/j.cortex.2016.03.019' target='_blank' class='black' title='View PDF of this article (postprint).'>
<img src='logos/author-logos/sprite-icons/pdf.png' class='pdf-icon transparent full-text'></a> </div><div class='article-type-line'>
<span class='label label-info-black'
title='Article reports original empirical observations (not directly comparable to previous research'>Original</span> <span class='label label-info-red'><a href='https://osf.io/jkh56/' target='_blank' class='black'
title='Go to Registered Report preregistered study protocol.'>Registered Report</a></span>
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<a href='#10.1016/j.cortex.2016.03.019'><i class='fas fa-link link-button'></i></a>
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<div class='article-title'>Mu suppression – A good measure of the human mirror neuron system?</div>
<div class='author-text'>Hobson & Bishop (2016)</div>
<div class='journal-text'>Cortex</div> <div class='doi-dimmed'> <a href='https://dx.doi.org/10.1016/j.cortex.2016.03.019' target='_blank' class='doi-dimmed grey'>10.1016/j.cortex.2016.03.019</a></div><br><div class='transparency-line'><div style='display:inline;' class='popUpOnHover'>
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<div class='abstractText minimize'>Mu suppression has been proposed as a signature of the activity of the human mirror neuron system. However the mu frequency band (8-13 Hz) overlaps with the alpha frequency band, which is sensitive to attentional fluctuation, and thus mu suppression could potentially be confounded by changes in attentional engagement. The specific baseline against which mu suppression is assessed may be crucial, yet there is little consistency in how this is defined. We examined mu suppression in 61 typical adults, the largest mu suppression study so far conducted. We compared different methods of baselining, and examined activity at central and occipital electrodes, to both biological (hands) and non-biological (kaleidoscope) moving stimuli, to investigate the involvement of attention and alpha activity in mu suppression. We also examined changes in beta power, another candidate index of mirror neuron system engagement. We observed strong mu suppression restricted to central electrodes when participants performed hand movements, demonstrating that mu is indeed responsive to the activity of the motor cortex. However, when we looked for a similar signature of mu suppression to passively observed stimuli, the baselining method proved to be crucial. Selective suppression for biological vs non-biological stimuli was seen at central electrodes only when we used a within-trial baseline based on a static stimulus: this method greatly reduced trial-by-trial variation in the suppression measure compared with baselines based on blank trials presented in separate blocks. Even in this optimal condition, 16-21% of participants showed no mu suppression. Changes in beta power also did not match our predicted pattern for mirror neuron system engagement, and did not seem to offer a better measure than mu. Our conclusions are in contrast to those of a recent meta-analysis, which concluded that mu suppression is a valid means to examine mirror neuron activity. We argue that mu suppression can be used to index the human mirror neuron system, but the effect is weak and unreliable and easily confounded with alpha suppression.</div><div class='secondary-section'>
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<div class='article-title'>A series of meta-analytic tests of the efficacy of long-term psychoanalytic psychotherapy</div>
<div class='author-text'>Woll & Schönbrodt (2018)</div>
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<div class='abstractText minimize'>Recent meta-analyses come to conflicting conclusions about the efficacy of long-term psychoanalytic psychotherapy (LTPP). Our first goal was to reproduce the most recent meta-analysis by Leichsenring, Abbass, Luyten, Hilsenroth, and Rabung (2013) who found evidence for the efficacy of LTPP in the treatment of complex mental disorders. Our replicated effect sizes were in general slightly smaller. Second, we conducted an updated meta-analysis of randomized controlled trials comparing LTPP (lasting for at least one year and 40 sessions) to other forms of psychotherapy in the treatment of complex mental disorders. We focused on a transparent research process according to open science standards and applied a series of elaborated meta-analytic procedures to test and control for publication bias. Our updated meta-analysis comprising 191 effect sizes from 14 eligible studies revealed small, statistically significant effect sizes at post-treatment for the outcome domains psychiatric symptoms, target problems, social functioning, and overall effectiveness (Hedges’ g ranging between 0.24 and 0.35). The effect size for the domain personality functioning (0.24) was not significant (p = .08). No signs for publication bias could be detected. In light of a heterogeneous study set and some methodological shortcomings in the primary studies, these results should be interpreted cautiously. In conclusion, LTPP might be superior to other forms of psychotherapy in the treatment of complex mental disorders. Notably, our effect sizes represent the additional gain of LTPP vs. other forms of primarily long-term psychotherapy. In this case, large differences in effect sizes are not to be expected.</div><div class='secondary-section'>
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<div class='article-title'>Does sadness impair color perception? Flawed evidence and faulty methods</div>
<div class='author-text'>Holcombe, Brown, Goodbourn, Etz, & Geukes (2016)</div>
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