8,902 Matching Annotations
  1. Jun 2020
    1. 2020-06-01

    2. Health, T. L. G. (2020). Publishing in the time of COVID-19. The Lancet Global Health, 8(7), e860. https://doi.org/10.1016/S2214-109X(20)30260-6

    3. It is difficult to imagine an organisation or individual that has not been affected by the COVID-19 pandemic. As we as a journal begin our fourth month of operating from makeshift home workspaces, perhaps it is time to reflect on our own experiences so far and how they might shape the future of this and other journals.
    4. 10.1016/S2214-109X(20)30260-6
    5. Publishing in the time of COVID-19
    1. 2020-04-06

    2. Social distancing is vital to mitigate the spread of the novel coronavirus. We use geolocation data to document that political beliefs present a significant limitation to the effectiveness of state-level social distancing orders. Residents in Republican counties are less likely to completely stay at home after a state order has been implemented relative to those in Democratic counties. Debit card transaction data shows that Democrats are more likely to switch to e-commerce spending after state orders are implemented. We also find that Democrats are less likely to respond to a state-level order when it is issued by a Republican governor relative to one issued by a Democratic governor. These results are robust to controlling for other factors including time, geography, local COVID-19 cases and deaths, county characteristics, and other social distancing orders. We conclude that bipartisan support is essential to maximize the effectiveness of social distancing orders.
    3. Political Beliefs affect Compliance with COVID-19 Social Distancing Orders
    1. 2020-04-23

    2. Voluntary physical distancing is essential for preventing the spread of COVID-19. Political partisanship may influence individuals’ responsiveness to recommendations from political leaders. Daily mobility during March 2020 was measured using location information from a sample of mobile phones in 3,100 US counties across 49 states. Governors’ Twitter communications were used to determine the timing of messaging about COVID-19 prevention. Regression analyses examined how political preferences influenced the association between governors’ COVID-19 communications and residents’ mobility patterns. Governors’ recommendations for residents to stay at home preceded stay-at-home orders, and led to a significant reduction in mobility that was comparable to the effect of the orders themselves. Effects were larger in Democratic than Republican-leaning counties, a pattern more pronounced under Republican governors. Democratic-leaning counties also responded more to recommendations from Republican than Democratic governors. Political partisanship influences citizens’ decisions to voluntarily engage in physical distancing in response to communications by their governor.
    3. Political Partisanship Influences Behavioral Responses to Governors’ Recommendations for COVID-19 Prevention in the United States
    1. 2020-06-16

    2. Anne has been hooked on the "replication crisis" in psychology for some time, switching from infant research to focus on meta-science. A switch we’re all glad she made. A PhD Student under Daniël Lakens’, she is part of the project "Increasing the reliability and efficiency of psychological science" at Eindhoven University of Technology. On any open science topic Anne is an expert, but today she will talk on Registered Reports, which is what I hope to become the default approach to conducting research.
    3. King's Open Research Conference | Anne Scheel | The Importance of Registered Reports
    1. 2020-06-17

    2. Długosz, P. (2020). Neurotic coronavirus generation? The report from the second wave of research on the students from Kraków [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/6ecr7

    3. 10.31234/osf.io/6ecr7
    4. The report presents the results of the second wave of research conducted among the students of the Pedagogical University of Kraków. The research method was an on-line survey (CAWI) on the sample of 1927 respondents. The comparison of responses from both surveys indicates that the change in attitudes and mental condition of the respondents occurred. After almost three months of quarantine the youth is less interested in the pandemic, has lower fear of the coronavirus, evaluates the actions taken by government to combat the pandemic worse. A decrease in satisfaction with their lives and an increase in the symptoms of stress is also observed. Negative emotions of anxiety, sadness, exhaustion and loneliness are also dominant among youth. The psychological resources were exploited to a relatively small extent. The adaptive reactions remain on a similar level. Among the respondents active combating of the threats and redirecting their attention as well as comforting oneself that it could have been worse are dominant. The respondents reveal the symptoms of burnout with remote education. Mental tiredness, decreased efficiency of actions and a decrease in motivation for learning are observed as well.
    5. Neurotic coronavirus generation? The report from the second wave of research on the students from Kraków
    1. 2020-06-15

    2. Zelner, J., Riou, J., Etzioni, R., & Gelman, A. (2020). Accounting for Uncertainty During a Pandemic. ArXiv:2006.08745 [Physics, q-Bio, Stat]. http://arxiv.org/abs/2006.08745

    3. 2006.08745
    4. We discuss several issues of statistical design, data collection, analysis, communication, and decision making that have arisen in recent and ongoing coronavirus studies, focusing on tools for assessment and propagation of uncertainty. This paper does not purport to be a comprehensive survey of the research literature; rather, we use examples to illustrate statistical points that we think are important.
    5. Accounting for Uncertainty During a Pandemic
    1. 2020-04-15

    2. Tips on Using Science Twitter During COVID-19. (2020, April 15). PLOS SciComm. https://scicomm.plos.org/2020/04/15/tips-on-using-science-twitter-during-covid-19/

    3. In the middle of the COVID-19 pandemic, many scientists have taken to social media platforms, particularly Twitter. Social media can facilitate research collaboration, generate ideas, clarify misinformation, and further understanding. Here are some of the ways that science is happening on Twitter, including strategies to extend the reach of ideas or ask others for help. While most of these examples address the urgent pandemic, they will work in ordinary times as well.
    4. Tips on Using Science Twitter During COVID-19
    1. 2020-05-24

    2. Tomorrow at 1pm CEST I'll be doing a virtual talk for the Rotterdam R.I.O.T. Science Club (@rdam_riots) on using Twitter for science I'll be covering both the *why* and the *how* + I'll be leaving plenty of time for a Q&A session. Watch here: https://tinyurl.com/y7uoe4ls
    1. Service, B. W. (n.d.). Fire Danger—Province of British Columbia. Province of British Columbia. Retrieved June 17, 2020, from https://www2.gov.bc.ca/gov/content/safety/wildfire-status/wildfire-situation/fire-danger

    2. Weather has a significant impact on wildfires – in how they start, how aggressively they spread, and how long they burn. Find out the current fire danger rating in your area and other information about fire weather. The BC Wildfire Service operates about 260 weather stations, which send reports on an hourly basis. These hourly weather observations, supplemented by data from other agency stations, support fire weather forecasting and the Canadian Forest Fire Danger Rating System (CFFDRS).
    3. Fire Danger
    1. The United Kingdom Terror Threat Levels, often referred to as UK Threat Levels, are the alert states that have been in use since 1 August 2006 by the British government to warn of forms of terrorist activity. Before then a colour-based alert scheme known as BIKINI state was used.[1] The response indicates how government departments and agencies and their staffs should react to each threat level.
    2. UK Threat Levels
    1. Welcome to my lab | Steve Lindsay’s Lab. (n.d.). Retrieved June 17, 2020, from http://web.uvic.ca/~dslind/

    2. I'm a cognitive psychologist. Most of my research explores human memory. I am especially interested in determinants of the subjective experience of remembering, source monitoring (the inferential processes by which people identify the origins of mental events such as memories), and the application of theories concerning these processes to everyday memory phenomena (e.g., eyewitness evidence). I collaborate with several terrific psychologists, and I have had the great pleasure of working with many wonderful students at both the undergraduate and graduate levels. Check out my Google Scholar profile.
    3. Steve Lindsay's Lab
    1. 2020-06-08

    2. Philip N. Cohen gives an overview of the scientific information ecosystem in the context of COVID-19, with an emphasis on the role of preprints. The slides are available here: https://osf.io/5mue7/.
    3. COVID-19, preprints, and the information ecosystem
    1. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker
    2. In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. While the research community increasingly recognizes dynamic document generation and version management as tools to ensure reproducibility, we demonstrate with practical examples that these alone are not sufficient to ensure long-term computational reproducibility. Combining containerization, dependence management, version management, and dynamic document generation, the proposed workflow increases scientific productivity by facilitating later reproducibility and reuse of code and data.
    1. 2020-06-12

    2. Morey, R. D. (2020, June 12). Power and precision. Medium. https://medium.com/@richarddmorey/power-and-precision-47f644ddea5e

    3. One of the common claims of anti-significance-testing reformers is that power analysis is flawed, and that we should be planning for study “precision” instead. I think this is wrong for several reasons that I will outline here. In summary:“Precision” is not itself a primitive theoretical concept. It is an intuition that is manifest through other more basic concepts, and it is those more basic concepts that we must understand.Precision can be thought of as the ability to avoid confusion between closeby regions of the parameter space. When we define power properly, we see that power is directly connected to precision. We don’t replace power with precision; we explain precision using power.Expected CI width (which some associate with “precision”) can depend on the parameter value, except in special cases. Power analysis directs your attention to a specific area of interest, linked to the purpose of the study, and hence overcomes this problem with CI-only concepts of precision.(One-tailed) Power is a flexible way of thinking about precision; confidence intervals (CIs), computed with equal probability in each tail, have difficulties with error trade-offs (asymmetricly-tailed CIs, though possible, would surely confuse people). We should thus keep the concept of power, and explain CIs and precision using confusion/error as the primitives.
    4. Power and precision
    1. 10.21428/ba67f642.0499afe0
    2. With each major crisis, be it war, pandemic, or major new technology, there has been a need to reinvent the relationships between individuals, businesses, and governments. Today's pandemic, joined with the tsunami of data, crypto and AI technologies, is such a crisis. Consequently the critical question for today is: what sort institutions should we be creating both to help us past this crisis and to make us less vulnerable to the next crisis? This book lays out a vision of what we should build, covering not only how to reforge our societies' social contract but also how institutions, systems, infrastructure, and law should change in support of this new order. We invite your comments and suggestions on both the ideas and the presentation, preferably by June 1, 2020 when we will move to make the book more widely available.
    3. Building the New Economy
    1. 2020-06-15

    2. Devi Sridhar on Twitter: “Feels like England has lost the plot & can’t see the wood for the trees. Obsessing over 1m v. 2m (tbh, restaurants/pubs not financially viable at either), mandatory masks -> instead of larger questions of what is the objective & necessary strategy? How best to prepare for winter?” / Twitter. (n.d.). Twitter. Retrieved June 16, 2020, from https://twitter.com/devisridhar/status/1272464161025523717

    3. Feels like England has lost the plot & can't see the wood for the trees. Obsessing over 1m v. 2m (tbh, restaurants/pubs not financially viable at either), mandatory masks -> instead of larger questions of what is the objective & necessary strategy? How best to prepare for winter?
    1. 2020-06-08

    2. In a desperate search for a boost, he could release a coronavirus vaccine that has not been shown to be safe and effective as an October surprise.
    3. Could Trump Turn a Vaccine Into a Campaign Stunt?
    1. 2020-05

    2. Brodeur, A., Cook, N., & Heyes, A. (2020). A Proposed Specification Check for p-Hacking. AEA Papers and Proceedings, 110, 66–69. https://doi.org/10.1257/pandp.20201078

    3. 10.1257/pandp.20201078
    4. We propose a specification check for p-hacking. More specifically, we advocate the reporting of t-curves and mu-curves—the t-statistics and estimated effect sizes derived from regressions using every possible combination of control variables from the researcher's set—and introduce a standardized and accessible implementation. Our specification check allows researchers, referees, and editors to visually inspect variation in effect sizes, significativity, and sensitivity to the inclusion of control variables. We provide a Stata command that implements the specification check. Given the growing interest in estimating causal effects, the potential applicability of this specification check to empirical studies is large.
    5. A Proposed Specification Check for p-Hacking
    1. 2020-05

    2. Ofosu, G. K., & Posner, D. N. (2020). Do Pre-analysis Plans Hamper Publication? AEA Papers and Proceedings, 110, 70–74. https://doi.org/10.1257/pandp.20201079

    3. 10.1257/pandp.20201079
    4. Scholars assert that pre-analysis plans (PAPs) generate boring, lab-report style papers and thus hamper publication. We test this claim by comparing the publication rates of experimental NBER working papers with and without PAPs. We find that articles with PAPs are slightly less likely to be published. However, conditional on being published, PAP-generated papers are significantly more likely to land in top-five journals. Also, PAP-based journal articles generate more citations. Our findings suggest that the alleged trade-off between career concerns and the scientific credibility that comes from registering and adhering to a PAP is less stark than is sometimes alleged.
    5. Do Pre-analysis Plans Hamper Publication?
    1. 2020-06-12

    2. The south west of England has the highest rate of coronavirus spread in the UK, with an “R number” estimated to be in the range of 0.8 to 1.1. Most other regions in England have R numbers whose range goes up to 1, according to government figures released today that provide regional R values for the first time.
    3. First coronavirus R numbers for regions within England released
    1. 2020-06-13

    2. ☣️ Michael Ç̸̠͎͉̹̼̠͔̗̓̐̐̓̓̀͝͝. Bazaco ☣️ on Twitter: “The amount of experts who used to cry foul about people acting like experts in their field that have now chased the COVID story pretending to be virologists, ID epidemiologists, ID physicians, and/or infection control specialists to try and brand build is creepy and ghoulish. 😑” / Twitter. (n.d.). Twitter. Retrieved June 15, 2020, from https://twitter.com/mcbazacophd/status/1271597829065187328

    3. Example of someone who knows what she is talking about (Dr. Grabowski), and someone who is (and has been for months) brand building off hyperbole and doesn’t know the science at all:
    4. Also, anyone telling you that they ‘absolutely know the answer’ to COVID questions is a liar and you should run away.
    5. The amount of experts who used to cry foul about people acting like experts in their field that have now chased the COVID story pretending to be virologists, ID epidemiologists, ID physicians, and/or infection control specialists to try and brand build is creepy and ghoulish.
    1. 2020-06-02

    2. COVID-19: Review of disparities in risks and outcomes. (n.d.). GOV.UK. Retrieved June 15, 2020, from https://www.gov.uk/government/publications/covid-19-review-of-disparities-in-risks-and-outcomes

    3. This is a descriptive review of data on disparities in the risk and outcomes from COVID-19. This review presents findings based on surveillance data available to PHE at thetime of its publication, including through linkage to broader health data sets. It confirmsthat the impact of COVID-19 has replicated existing health inequalities and, in somecases, has increased them. These results improve our understanding of the pandemicand will help in formulating the future public health response to it.
    4. Disparities in the risk and outcomes of COVID-19