Provides survival analysis functions with support for time-dependent 
    and subject-specific (e.g., propensity score) weighting. Implements weighted 
    estimation for Cox models, Kaplan-Meier survival curves, and treatment 
    differences with point-wise and simultaneous confidence bands. Includes 
    restricted mean survival time (RMST) comparisons evaluated across all 
    potential truncation times with both point-wise and simultaneous confidence 
    bands. See Cole, S. R. & Hernán, M. A. (2004) 
    <doi:10.1016/j.cmpb.2003.10.004> for methodological background.

Treemaps are a visually appealing graphical representation of
    numerical data using a space-filling approach. A plane or 'map' is
    subdivided into smaller areas called cells.  The cells in the map are
    scaled according to an underlying metric which allows to grasp the
    hierarchical organization and relative importance of many objects at
    once. This package contains two different implementations of treemaps,
    Voronoi treemaps and Sunburst treemaps.  The Voronoi treemap function
    subdivides the plot area in polygonal cells according to the highest
    hierarchical level, then continues to subdivide those parental cells
    on the next lower hierarchical level, and so on. The Sunburst treemap
    is a computationally less demanding treemap that does not require
    iterative refinement, but simply generates circle sectors that are
    sized according to predefined weights.  The Voronoi tesselation is
    based on functions from Paul Murrell (2012)
    <https://www.stat.auckland.ac.nz/~paul/Reports/VoronoiTreemap/voronoiTreeMap.html>.

Generates balancing weights for causal effect estimation in observational studies with
             binary, multi-category, or continuous point or longitudinal treatments by easing and
             extending the functionality of several R packages and providing in-house estimation methods.
             Available methods include those that rely on parametric modeling, optimization, and machine learning. Also
             allows for assessment of weights and checking of covariate balance by interfacing directly
             with the 'cobalt' package. Methods for estimating weighted regression models that take into account 
             uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how
             to install any package 'WeightIt' uses, including those that may not be on CRAN.