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      Exploring the association between compliance with measures to prevent the spread of COVID-19 and big five traits with Bayesian generalized linear model

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          Abstract

          Research has examined the association between people's compliance with measures to prevent the spread of COVID-19 and personality traits. However, previous studies were conducted with relatively small-size datasets and employed frequentist analysis that does not allow data-driven model exploration. To address the limitations, a large-scale international dataset, COVIDiSTRESS Global Survey dataset, was explored with Bayesian generalized linear model that enables identification of the best regression model. The best regression models predicting participants' compliance with Big Five traits were explored. The findings demonstrated first, all Big Five traits, except extroversion, were positively associated with compliance with general measures and distancing. Second, neuroticism, extroversion, and agreeableness were positively associated with the perceived cost of complying with the measures while conscientiousness showed negative association. The findings and the implications of the present study were discussed.

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          Bayesian inference for psychology. Part II: Example applications with JASP

          Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (http://www.jasp-stats.org), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.
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            Psychological Outcomes Associated with Stay-at-Home Orders and the Perceived Impact of COVID-19 on Daily Life

            Highlights • Examined impact of COVID-19 and stay-at-home orders on psychological outcomes. • Stay-at-home orders linked to health anxiety, financial worry, and loneliness. • Impact of COVID-19 on life associated with health anxiety and financial worry. • Impact of COVID-19 on life associated with less loneliness and more social support. • Results highlight importance of social connection and need for tele-mental health.
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              Best-Practice Recommendations for Defining, Identifying, and Handling Outliers

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                Author and article information

                Journal
                Pers Individ Dif
                Pers Individ Dif
                Personality and Individual Differences
                Elsevier Ltd.
                0191-8869
                0191-8869
                23 February 2021
                July 2021
                23 February 2021
                : 176
                : 110787
                Affiliations
                Educational Psychology Program, University of Alabama, United States of America
                Author notes
                [* ]University of Alabama, Box 870231, Tuscaloosa, AL 35487, United States of America.
                Article
                S0191-8869(21)00162-8 110787
                10.1016/j.paid.2021.110787
                7901385
                33642661
                1c6c23c9-4765-45a8-a6b8-9b1a557c95ee
                © 2021 Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 12 January 2021
                : 14 February 2021
                : 18 February 2021
                Categories
                Article

                Clinical Psychology & Psychiatry
                covid-19,preventive measures,physical distancing,social distancing,big five,big data,bayesian analysis,data-driven analysis

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