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  1. SciScore for 10.1101/2022.05.05.22274721: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationThe latter is a negative control outcome, where if selection were random, there should be no difference in risk factor estimates between tested (true) negative participants and untested (assumed) negative participants.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are limitations of these measures. These data were measured at UK Biobank baseline, up to 14 years before the pandemic began (years 2006-2010). Whilst factors such as education (highest qualification) are unlikely to have changed in adults during this time, other measures (income and household size for example) may have changed. In sensitivity analyses removing retired individuals from income analyses, we could only exclude individuals retired at baseline. Whilst this will be correlated with income at baseline, we could not unpick how current employment status was associated with COVID-19. Further, we could not examine how associations with occupation, which has been shown to be associated with COVID-19, have changed over time. Whilst some occupation data are available, we do not have access to i) self-employment status or ii) The National Statistics Socio-economic classification codes which can be used to proxy SEP. UK Biobank is healthier and wealthier than the general population,19 and as such, the point estimates obtained here may not be transportable to other populations. Whilst UK Biobank has relatively little missing data, some variables (e.g., income) experience high amounts of missingness, which we did not account for. Multiple imputation offers an opportunity to account for missing data in analyses, however, this method is only valid where data are missing at random. Here, it is plausible to assume that missingness in the reporting of income is missing not at ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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