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).

Create and manipulate study cohorts in data mapped to the 
    Observational Medical Outcomes Partnership Common Data Model.

Generate cohorts and subsets using an Observational 
  Medical Outcomes Partnership (OMOP) Common Data Model (CDM) Database. 
  Cohorts are  defined using 'CIRCE' (<https://github.com/ohdsi/circe-be>) or 
  SQL compatible with 'SqlRender' (<https://github.com/OHDSI/SqlRender>).

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.

Calculating crude sequence ratio, adjusted sequence ratio and 
    confidence intervals using data mapped to the Observational Medical 
    Outcomes Partnership Common Data Model.

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.