Simplifies regression modeling in R by integrating multiple modeling and summarization
  tools into a cohesive, user-friendly interface. Designed to be accessible for researchers,
  particularly those in Low- and Middle-Income Countries (LMIC). Built upon widely accepted 
  statistical methods, including logistic regression (Hosmer et al. 2013, ISBN:9781118548429), 
  log-binomial regression (Spiegelman and Hertzmark 2005 <doi:10.1093/aje/kwi188>), 
  Poisson and robust Poisson regression (Zou 2004 <doi:10.1093/aje/kwh090>), 
  negative binomial regression (Hilbe 2011, ISBN:9780521179515), and linear regression 
  (Kutner et al. 2005, ISBN:9780071122214). Leverages multiple dependencies to ensure 
  high-quality output and generate reproducible, publication-ready tables in alignment with
  best practices in epidemiology and applied statistics.

Connects to the 'Google Trends for Health' API hosted at
    <https://trends.google.com/trends/>, allowing projects authorized to use the
    health research data to query 'Google Trends'.

An interface for retrieving and displaying the information
        returned online by Google Trends is provided. Trends (number of
        hits) over the time as well as geographic representation of the
        results can be displayed.

A collection of functions for testing randomness (or mutual independence) in linear and circular data as proposed in Gehlot and Laha (2025a) <doi:10.48550/arXiv.2506.21157> and Gehlot and Laha (2025b) <doi:10.48550/arXiv.2506.23522>, respectively.

Creates presentation-ready tables summarizing data sets,
    regression models, and more. The code to create the tables is concise
    and highly customizable. Data frames can be summarized with any
    function, e.g. mean(), median(), even user-written functions.
    Regression models are summarized and include the reference rows for
    categorical variables. Common regression models, such as logistic
    regression and Cox proportional hazards regression, are automatically
    identified and the tables are pre-filled with appropriate column
    headers.