Wraps the 'AntiWord' utility to extract text from Microsoft Word 
    documents. The utility only supports the old 'doc' format, not the new xml 
    based 'docx' format. Use the 'xml2' package to read the latter.

Data from the anxiety and confinement study from Alvarado-Aravena et al. (2022) <doi:10.3390/bs12100398>.

You can use this package to create custom pipeline badges in a standard 'svg' format.
    This is useful for a company to use internally, where it may not be possible
    to create badges through external providers.
    This project was inspired by the 'anybadge' library in python.

Supplies a set of functions to query air travel data for user-
    specified years and airports. Datasets include on-time flights, airlines,
    airports, planes, and weather.

Made to make your life simpler with packages, by
    installing and loading a list of packages, whether they are on CRAN,
    Bioconductor or github. For github, if you do not have the full path, with 
    the maintainer name in it (e.g. "achateigner/topReviGO"), it will be able to
    load it but not to install it.

Convert input in any one of character, integer, numeric, factor,
 or ordered type into 'POSIXct' (or 'Date') objects, using one of a number of
 predefined formats, and relying on Boost facilities for date and time parsing.

An iterative process that optimizes a function by alternately 
    performing restricted optimization over parameter subsets. Instead of joint 
    optimization, it breaks the optimization problem down into simpler 
    sub-problems. This approach can make optimization feasible when joint 
    optimization is too difficult.

To address the violation of the assumption of normally distributed variables, researchers frequently employ bootstrapping. Building upon established packages for R (Sigmann et al. (2024) <doi:10.32614/CRAN.package.afex>, Lenth (2024) <doi:10.32614/CRAN.package.emmeans>), we provide bootstrapping functions to approximate a normal distribution of the parameter estimates for between-subject, within-subject, and mixed one-way and two-way ANOVA.