Diffusion Weighted Imaging (DWI) is a Magnetic Resonance Imaging
             modality, that measures diffusion of water in tissues like the human
             brain. The package contains R-functions to process diffusion-weighted
             data. The functionality includes diffusion tensor imaging (DTI),
             diffusion kurtosis imaging (DKI), modeling for high angular resolution
             diffusion weighted imaging (HARDI) using Q-ball-reconstruction and
             tensor mixture models, several methods for structural adaptive
             smoothing including POAS and msPOAS, and a streamline fiber tracking
             for tensor and tensor mixture models.
             The package provides functionality to manipulate and visualize results
             in 2D and 3D.

A tool to calculate the correlation boundary for the correlation between the response rate and the log-rank test statistic for the binary surrogate endpoint and the time-to-event primary endpoint, as well as conduct simulation studies to obtain design operating characteristics of the drop-the-losers design.

Create high-performance clinical reporting tables (TLGs) from
    ADaM-like inputs. The package provides a consistent, programmatic API
    to generate common tables such as demographics, adverse event incidence,
    and laboratory summaries, using 'data.table' for fast aggregation over
    large populations. Functions support flexible target-variable selection,
    stratification by treatment, and customizable summary statistics, and
    return tidy, machine-readable results ready to render with downstream
    table/formatting packages in analysis pipelines.

Allows humanitarian community, academia, media, government, and non-governmental organizations to utilize the data collected by the 'Displacement Tracking Matrix' (<https://dtm.iom.int>), a unit in the International Organization for Migration. This also provides non-sensitive Internally Displaced Person figures, aggregated at the country, Admin 1 (states, provinces, or equivalent), and Admin 2 (smaller administrative areas) levels.