Top 10 Psyarxiv Papers Today


2.022 Mikeys
#1. No compelling evidence that women with more attractive faces show stronger preferences for masculine men
Ciaran Docherty, Anthony J Lee, Amanda Hahn, Benedict C. Jones
Many researchers have suggested that more attractive women will show stronger preferences for masculine men, potentially because such women are better placed to offset the potential costs of choosing a masculine mate. Perhaps the most compelling evidence for this proposal has come from work reporting a positive association between third-party ratings of women’s facial attractiveness and women’s preference for masculinized versus feminized versions of men’s faces as hypothetical long-term partners. Because this finding was based on only a small sample of women (N = 35), we attempted to replicate this result in a much larger sample (N = 454). We found that women, on average, preferred masculinized versions of men’s faces to feminized versions and that this masculinity preference was slightly stronger when women assessed men’s attractiveness as short-term, rather than long-term, mates. However, we found no compelling evidence that women’s masculinity preferences were related to their own attractiveness. These results underline the...
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DegenRolf: Good looking women don't show any greater preference for masculine men, failing to replicate an influential psychology study. https://t.co/2DwReOZtJV https://t.co/Y1WXG9dFed
Ben_C_J: New preprint. In the biggest study to date, we find no compelling evidence that more attractive women demonstrate stronger preferences for masculine men. Secondary data analysis led by new student @CiaranDocherty6. https://t.co/OEtfeLDqIM data + code: https://t.co/CbdVXAWjme https://t.co/BAFyb1koBq
momentumyy: やっぱしか No compelling evidence that women with more attractive faces show stronger preferences for masculine men https://t.co/z79iCLoM99
mezakrp: oh boy! https://t.co/MyMTOzeLsT https://t.co/9lv5ZmPzZn
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2.019 Mikeys
#2. INCORPORATING SENSIBILITY AND SPECIFICITY IN STATISTICAL INFERENCE IN EPIDEMIOLOGY OF DEPRESSION
Gabriel González-Medina
Confidence intervals are calculated no considering measurement error, for this reason, statistical inference is only made considering sample error. Particularly, estimation of prevalence is very important in epidemiology because the government needs to consider a likely population to provide enough treatment, however, these estimations are conservative because of standardized questionnaires have a greater probability to no identify true cases in comparison to identify false cases. In this sense, sensibility and specificity generate asymmetry in measurement error, besides asymmetry in confidence interval.
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Gabriel00602805: I could glad if any feedback in this #draft #preprint #psychology "methods #statatistics if some one want to write with me i will be happy INCORPORATING SENSIBILITY AND SPECIFICITY IN STATISTICAL INFERENCE IN EPIDEMIOLOGY https://t.co/id5nsvZLSM vía @OSFramework
PsyArXivBot: INCORPORATING SENSIBILITY AND SPECIFICITY IN STATISTICAL INFERENCE IN EPIDEMIOLOGY OF DEPRESSION https://t.co/UFt0zxYPGH
Neurofrogg: RT @PsyArXivBot: INCORPORATING SENSIBILITY AND SPECIFICITY IN STATISTICAL INFERENCE IN EPIDEMIOLOGY OF DEPRESSION https://t.co/UFt0zxYPGH
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2.016 Mikeys
#3. Book review of "Web chosa no kagaku"
Asako Miura
Book review of "Web chosa no kagaku" for Sociological Theory and Methods. You can see detailed info of the book in http://www.asakura.co.jp/books/isbn/978-4-254-12228-2/.
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asarin: 『ウェブ調査の科学』(朝倉書店)の書評を書きました.来年3月に「理論と方法」誌に掲載される予定です.https://t.co/O741bLWc4K
PsyArXivBot: Book review of "Web chosa no kagaku" https://t.co/hHrrpWqL4Q
flurry: RT @asarin: 『ウェブ調査の科学』(朝倉書店)の書評を書きました.来年3月に「理論と方法」誌に掲載される予定です.https://t.co/O741bLWc4K
eiji_kawano: RT @asarin: 『ウェブ調査の科学』(朝倉書店)の書評を書きました.来年3月に「理論と方法」誌に掲載される予定です.https://t.co/O741bLWc4K
yuichi_ichihara: RT @asarin: 『ウェブ調査の科学』(朝倉書店)の書評を書きました.来年3月に「理論と方法」誌に掲載される予定です.https://t.co/O741bLWc4K
twremcat: RT @asarin: 『ウェブ調査の科学』(朝倉書店)の書評を書きました.来年3月に「理論と方法」誌に掲載される予定です.https://t.co/O741bLWc4K
BluesNoNo: RT @asarin: 『ウェブ調査の科学』(朝倉書店)の書評を書きました.来年3月に「理論と方法」誌に掲載される予定です.https://t.co/O741bLWc4K
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2.013 Mikeys
#4. Understanding and reducing the spread of misinformation online
Gordon Pennycook, Ziv Epstein, Mohsen Mosleh, Antonio Alonso Arechar, Dean Eckles, David Rand
The spread of false and misleading news on social media is of great societal concern. Why do people share such content, and what can be done about it? In a first survey experiment (N=1,015), we demonstrate a dissociation between accuracy judgments and sharing intentions: even though true headlines are rated as much more accurate than false headlines, headline veracity has little impact on sharing. We argue against a “post-truth” interpretation, whereby people deliberately share false content because it furthers their political agenda. Instead, we propose that the problem is simply distraction: most people do not want to spread misinformation, but are distracted from accuracy by other salient motives when choosing what to share. Indeed, when directly asked, most participants say it is important to only share accurate news. Accordingly, across three survey experiments (total N=2775) and an experiment on Twitter in which we messaged N=5,482 users who had previously shared news from misleading websites, we find that subtly inducing...
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codykommers: People are able to spot fake news, but that's only one consideration in whether they share it. Most people want to share accurate info, but ~20% still feel it's okay not to. Asking about this changes tweeting behavior over time. @GordPennycook @DG_Rand https://t.co/y65uR10jJD
PsyArXivBot: Understanding and reducing the spread of misinformation online https://t.co/1m0UNLwEkf
mavadillo: RT @PsyArXivBot: Understanding and reducing the spread of misinformation online https://t.co/1m0UNLwEkf
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2.012 Mikeys
#5. How to embrace variation and accept uncertainty in linguistic and psycholinguistic data
Shravan Vasishth, andrew gelman
Data analysis in linguistics and related areas like psychology typically involves a binary decision: either reject or accept the null hypothesis. This frequentist data-analytic approach has not only been widely misused, but also does not lead to any decisive conclusions, particularly when statistical power is low. Using an example from psycholinguistics, an alternative approach is demonstrated for reporting whether the data are consistent with a theoretical prediction or not. The key here is to focus on uncertainty quantification, and to learn to accept the fact that that we can often only draw uncertain conclusions from data. A focus on uncertainty quantification is likely to lead to fewer overly bold claims that, on closer investigation, may turn out to be not supported.
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shravanvasishth: New preprint with @StatModeling (submitted to a special issue): How to embrace variation and accept uncertainty in linguistic and psycholinguistic data. Comments and criticism are very welcome. https://t.co/avGD0qzXnM
PsyArXivBot: How to embrace variation and accept uncertainty in linguistic and psycholinguistic data https://t.co/Bav2KTEOdE
dimitrisbolis: RT @PsyArXivBot: How to embrace variation and accept uncertainty in linguistic and psycholinguistic data https://t.co/Bav2KTEOdE
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Total Words: 7052
Unqiue Words: 2111

2.01 Mikeys
#6. "Do the Right Thing" for Whom? An Experiment on Ingroup Favouritism, Group Assortativity and Moral Suasion
Ennio Bilancinio, Leonardo Boncinelli, Valerio Capraro, Tatiana Celadin, Roberto Di Paolo
In this paper we investigate the effect of moral suasion on ingroup favouritism. We report a well-powered, pre-registered, two-stage 2x2 mixed-design experiment. In the first stage, groups are formed on the basis of how participants answer to a set of questions, concerning non-morally relevant issues in one treatment (assortativity on non-moral preferences), and morally relevant issues in another treatment (assortativity on moral preferences). In the second stage, participants choose how to split a given amount of money between participants of their own group and participants of the other group, first in the baseline setting and then in a setting where they are told to do what they believe to be morally right (moral suasion). Our main results are: (i) in the baseline, participants tend to favour their own group to a greater extent when groups are assorted according to moral preferences, compared to when they are assorted according to non-moral preferences; (ii) the net effect of moral suasion is to decrease ingroup favouritism,...
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ValerioCapraro: Does moral suasion increase or decrease ingroup favouritism? - Overall, moral suasion decreases ingroup favouritism - But there's a non-negligible set of people for which moral suasion increases ingroup favouritism SSRN: https://t.co/YHKUKNkbjW PsyArXiv: https://t.co/cYloPRfeXg https://t.co/EFp83N41Zh
PsyArXivBot: "Do the Right Thing" for Whom? An Experiment on Ingroup Favouritism, Group Assortativity and Moral Suasion https://t.co/4NmSQDIjwf
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2.008 Mikeys
#7. Comparing unfamiliar voice and face identity perception using identity sorting tasks
Justine Johnson, Carolyn McGettigan, Nadine Lavan
Identity sorting tasks, where participants sort a number of naturally varying stimuli of usually two identities into perceived identities, have recently gained popularity in voice and face processing research. For both modalities, striking similarities in the results of these sorting tasks are apparent: Participants who are unfamiliar with the identities usually struggle to accurately perceive identities from these variable stimuli. They tend to perceive multiple stimuli of the same identity as different people and thus fail to “tell people together”. These similarities in the reported results may suggest that modality-general mechanisms underpin the completion of sorting tasks. In the current study, participants completed a voice sorting and a face sorting task. Taking an individual differences approach, we therefore asked whether there is a relationship between participants’ performance on voice and face sorting of unfamiliar identities. Participants additionally completed a voice discrimination (Bangor Voice Matching Test) and...
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JEJjohns: Really excited to share my first #preprint on @psyarxiv: “Comparing unfamiliar voice and face identity perception using identity sorting tasks” with @c_mcgettigan and @nadinelavan. #Identityperception #voiceresearch #faceresearch. Available at https://t.co/XF9tbYy1XS Thread 1/7
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2.007 Mikeys
#8. Artificial neural networks reveal multivariate integration of information from multiple category-selective regions
Mengting Fang, Aidas Aglinskas, Yichen Li, Stefano Anzellotti
Human visual cortex is organized into regions that respond preferentially to different categories of objects (i.e. faces, bodies, artifacts, scenes). However, often people need to integrate information about objects from different categories to make inferences about the world. How does the brain integrate information represented in different category-selective regions? In this work, we investigated this question taking advantage of a new analysis approach. Using artificial neural networks, we modeled the multivariate statistical dependence between fMRI responses in different brain regions. Regions whose responses were predicted significantly better by a combination of multiple category-selective regions than by the best-predicting category-selective region taken individually were identified as integration hubs. We used this approach to analyze fMRI responses to complex dynamic stimuli (the movie Forrest Gump), and identified five integration hubs: 1) the posterior medial thalamus, 2) the middle cingulate gyrus, 3) the posterior...
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Multivariate Pattern Dependence Network

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2.006 Mikeys
#9. A Registered Report of Error-Related Negativity and Reward Positivity as Biomarkers of Depression: P-Curving the Evidence
Peter E. Clayson, Kaylie A. Carbine, Michael J. Larson
Performance-monitoring event-related brain potentials (ERPs), such as the error-related negativity (ERN) and reward positivity (RewP), are advocated as biomarkers of depression symptoms and risk. However, a recent meta-analysis indicated effect size heterogeneity in the ERN and RewP literatures. Hence, advocating these ERPs as biomarkers of depression might be premature or possibly misguided due to the selective reporting of significant analyses on the part of researchers (e.g., p-hacking or omission of non-significant findings). The present study quantified the degree of selective reporting and the evidential value for a true relationship between depression and ERN and RewP using a p-curve analysis. We predicted that the ERN and RewP literatures would fail to show evidential value for a relationship between each ERP and depression. Contrary to expectations, both literatures showed evidential value, albeit weak. The statistical power of the included ERN studies was between 20% and 25%, and the statistical power of the RewP was...
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NIMH_RDoC: 'A Registered Report of ERN and RewP as Biomarkers of Depression: P-Curving the Evidence' - https://t.co/boJRlCLw2s by @clayson_peter, Kaylie Carbine, & @mjlarson29 "....both literatures showed evidential value, albeit weak." https://t.co/0IlWQo1ORD
ugpavlov: RT @NIMH_RDoC: 'A Registered Report of ERN and RewP as Biomarkers of Depression: P-Curving the Evidence' - https://t.co/boJRlCLw2s by @clay…
clayson_peter: RT @NIMH_RDoC: 'A Registered Report of ERN and RewP as Biomarkers of Depression: P-Curving the Evidence' - https://t.co/boJRlCLw2s by @clay…
mjlarson29: RT @NIMH_RDoC: 'A Registered Report of ERN and RewP as Biomarkers of Depression: P-Curving the Evidence' - https://t.co/boJRlCLw2s by @clay…
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2.002 Mikeys
#10. A Computational Account of the Mechanisms Underlying Face Perception Biases in Depression
Fabian Soto, Rochelle Ann Stewart, Sanaz Hosseini, Jason Scott Hays, Christopher G Beevers
Here, we take a computational approach to understand the mechanisms underlying face perception biases in depression. Thirty participants diagnosed with Major Depressive Disorder and thirty healthy control participants took part in three studies involving recognition of identity and emotion in faces. We used signal detection theory to determine whether any perceptual biases exist in depression aside from decisional biases. We found lower sensitivity to happiness in general, and lower sensitivity to both happiness and sadness with ambiguous stimuli. Our use of highly-controlled face stimuli ensures that such asymmetry is truly perceptual in nature, rather than the result of studying expressions with inherently different discriminability. We found no systematic effect of depression on the perceptual interactions between face expression and identity, suggesting that depression is not associated with difficulty attending to one of these dimensions while filtering out the other. We show through simulation that the overall pattern of...
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SotoCCNLab: New preprint from our lab in collaboration with @cgbeevers: A computational account of the mechanisms underlying face perception biases in depression. Our first contribution to computational psychiatry: https://t.co/jYeVeyVJrv https://t.co/SHOHzw1ez7
JustinCaouette: RT @PsyArXivBot: A Computational Account of the Mechanisms Underlying Face Perception Biases in Depression https://t.co/9Sgmdu2D6D
PhilCorlett1: RT @PsyArXivBot: A Computational Account of the Mechanisms Underlying Face Perception Biases in Depression https://t.co/9Sgmdu2D6D
ayumu_tomaru: RT @PsyArXivBot: A Computational Account of the Mechanisms Underlying Face Perception Biases in Depression https://t.co/9Sgmdu2D6D
BillyJansson: RT @PsyArXivBot: A Computational Account of the Mechanisms Underlying Face Perception Biases in Depression https://t.co/9Sgmdu2D6D
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