A generalised workflow for Matching-Adjusted Indirect
    Comparison (MAIC) analysis, which supports both anchored and
    non-anchored MAIC methods.  In MAIC, unbiased trial outcome comparison
    is achieved by weighting the subject-level outcomes of the
    intervention trial so that the weighted aggregate measures of
    prognostic or effect-modifying variables match those of the comparator
    trial. Measurements supported include time-to-event (e.g., overall
    survival) and binary (e.g., objective tumor response). The method is
    described in Signorovitch et al. (2010)
    <doi:10.2165/11538370-000000000-00000> and Signorovitch et al. (2012)
    <doi:10.1016/j.jval.2012.05.004>.

Collect  your data on digital marketing campaigns from Mailchimp using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

Perform a mail merge (mass email) using the message defined in 
    markdown, the recipients in a 'csv' file, and gmail as the mailing engine. 
    With this package you can parse markdown documents as the body of email, and 
    the 'yaml' header to specify the subject line of the email.  Any '{}' braces 
    in the email will be encoded with 'glue::glue()'. You can preview the email 
    in the RStudio viewer pane, and send (draft) email using 'gmailr'.

Interface to Apache Commons Email to send emails
    from R.

Allows the user to generate a friendly user interface for emails sending. 
    The user can choose from the most popular free email services ('Gmail', 'Outlook', 'Yahoo') and his default email application. 
    The package is a wrapper for the 'Mailtoui' 'JavaScript' library.  See <https://mailtoui.com/#menu> for more information.

Shiny for Open Science to visualize, share, and inventory the
    main existing human datasets for researchers.

Implements methodologies for modelling interval data by Normal
    and Skew-Normal distributions, considering appropriate parameterizations of
    the variance-covariance matrix that takes into account the intrinsic nature of
    interval data, and lead to four different possible configuration structures.
    The Skew-Normal parameters can be estimated by maximum likelihood, while Normal
    parameters may be estimated by maximum likelihood or robust trimmed maximum
    likelihood methods.