Provides access to well-documented medical datasets for teaching.
    Featuring several from the Teaching of Statistics in the Health Sciences 
    website <https://www.causeweb.org/tshs/category/dataset/>, a few reconstructed datasets of historical significance in medical
    research, some reformatted and extended from existing R packages, 
    and some data donations.

Generates risk estimates and comorbidity flags from ICD-9-CM
    codes available in administrative medical datasets. The package supports
    the Charlson Comorbidity Index, the Elixhauser Comorbidity
    classification, the Revised Cardiac Risk Index, and the Risk Stratification
    Index.  Methods are table-based, fast, and use the 'plyr' package, so
    parallelization is possible for large jobs. Also includes a sample of
    real ICD-9 data for 100 patients from a publicly available dataset.

Publicly available data from Medicare frequently requires extensive
    initial effort to extract desired variables and merge them; this package
    formalizes the techniques I've found work best. More information on the 
    Medicare program, as well as guidance for the publicly available data this package 
    targets, can be found on CMS's website covering publicly available data. See <https://www.cms.gov/Research-Statistics-Data-and-Systems/Research-Statistics-Data-and-Systems.html>.

Prints a random quote from Marcus Aurelius' book Meditations.

Contains a dataset of morphological and structural features of 'Medicinal LEAves (MedLEA)'. The features of each species is recorded by manually viewing the medicinal plant repository available at (<http://www.instituteofayurveda.org/plants/>). You can also download repository of leaf images of 1099 medicinal plants in Sri Lanka.

Parses information from text files with specific utility aimed at pulling information from Med Associate's (MPC) files. These functions allow for further analysis of MPC files.

A collection of methods for large scale single mediator hypothesis
    testing. The six included methods for testing the mediation effect are Sobel's
    test, Max P test, joint significance test under the composite null hypothesis,
    high dimensional mediation testing, divide-aggregate composite null test,
    and Sobel's test under the composite null hypothesis. Du et al (2023) 
    <doi:10.1002/gepi.22510>.