A general-purpose toolkit for comparing any two data frames
    with optional 'CDISC' (Clinical Data Interchange Standards Consortium)
    validation for clinical trial data. Core comparison functions work on
    arbitrary datasets: variable-level and observation-level comparison, data
    type checking, metadata attribute analysis (types, labels, lengths,
    formats), missing value handling, key-based row matching, tolerance-based
    numeric comparisons, and group-wise comparisons. Optional z-score
    outlier detection is available when enabled. When working with clinical
    data, the package additionally
    validates 'SDTM' (Study Data Tabulation Model) and 'ADaM' (Analysis Data
    Model) datasets against CDISC standards (SDTM IG 3.3/3.4, ADaM IG
    1.1/1.2/1.3), automatically detecting domains and flagging non-conformant
    variables. Generates unified comparison reports in text or HTML format
    with interactive dashboards. For CDISC standards, see
    <https://www.cdisc.org/standards>.

Creation of interactive tables, listings and figures ('TLFs') 
  and associated report for exploratory analysis of data in a clinical trial, 
  e.g. for clinical oversight activities.
  Interactive figures include sunburst, treemap, scatterplot, line plot and
  barplot of counts data. 
  Interactive tables include table of summary statistics
  (as counts of adverse events, enrollment table) and listings.
  Possibility to compare data (summary table or listing) across two data batches/sets.
  A clinical data review report is created via study-specific configuration 
  files and template 'R Markdown' reports contained in the package.

Bayesian and ML Emax model fitting, graphics and simulation for clinical dose
    response.  The summary data from the dose response meta-analyses in  
    Thomas, Sweeney, and Somayaji (2014) <doi:10.1080/19466315.2014.924876> and
    Thomas and Roy (2016) <doi:10.1080/19466315.2016.1256229> 
    Wu, Banerjee, Jin, Menon, Martin, and Heatherington(2017) <doi:10.1177/0962280216684528> 
    are included 
    in the package.  The prior distributions for the Bayesian analyses default to
    the posterior predictive distributions derived from these references.