Common API for filtering data stored in different data models.
    Provides multiple filter types and reproducible R code.
    Works standalone or with 'shinyCohortBuilder' as the GUI for interactive Shiny apps.

Summarise and visualise the characteristics of patients in data 
    mapped to the Observational Medical Outcomes Partnership (OMOP) common data 
    model (CDM).

This software tool is designed to extract data from a randomized subset of individuals 
    within a cohort and make it available for exploration in a shiny application environment. It 
    retrieves date-stamped, event-level records from one or more data sources that represent patient 
    data in the Observational Medical Outcomes Partnership (OMOP) data model format. This tool 
    features a user-friendly interface that enables users to efficiently explore the extracted 
    profiles, thereby facilitating applications, such as reviewing structured profiles.

A collection of functions dedicated to simulating staggered entry platform 
    trials whereby the treatment under investigation is a combination of two 
    active compounds. In order to obtain approval for this combination therapy,
    superiority of the combination over the two active compounds and superiority
    of the two active compounds over placebo need to be demonstrated. 
    A more detailed description of the design can be found in 
    Meyer et al. <DOI:10.1002/pst.2194> and a manual in Meyer et al. <arXiv:2202.02182>.

Functions to simplify the process of preparing event and transaction for cohort analysis.

Estimate survival using data mapped to the Observational Medical Outcomes Partnership common data model. Survival can be estimated based on user-defined study cohorts.

Functions to make lifetables and to calculate hazard function estimate using Poisson regression model with splines. Includes function to draw simple flowchart of cohort study. Function boxesLx() makes boxes of transition rates between states. It utilizes 'Epi' package 'Lexis' data.