Facilitates performing matching adjusted indirect comparison
 (MAIC) analysis where the endpoint of interest is either time-to-event
 (e.g. overall survival) or binary (e.g. objective tumor response). The method
 is described by Signorovitch et al (2012) <doi:10.1016/j.jval.2012.05.004>.

A generalised workflow for Matching-Adjusted Indirect
    Comparison (MAIC) analysis, which supports both anchored and
    non-anchored MAIC methods.  In MAIC, unbiased trial outcome comparison
    is achieved by weighting the subject-level outcomes of the
    intervention trial so that the weighted aggregate measures of
    prognostic or effect-modifying variables match those of the comparator
    trial. Measurements supported include time-to-event (e.g., overall
    survival) and binary (e.g., objective tumor response). The method is
    described in Signorovitch et al. (2010)
    <doi:10.2165/11538370-000000000-00000> and Signorovitch et al. (2012)
    <doi:10.1016/j.jval.2012.05.004>.

Provides accessible, interactive visualizations through the 'MAIDR'
    (Multimodal Access and Interactive Data Representation) system. Converts
    'ggplot2' and Base R plots into accessible HTML/SVG formats with keyboard
    navigation, screen reader support, and 'sonification' capabilities. Supports
    bar charts (simple, grouped, stacked), histograms, line plots, scatter plots,
    box plots, violin plots, candlestick (OHLC) charts, heat maps,
    density/smooth curves, faceted plots,
    multi-panel layouts (including patchwork), and multi-layered plot combinations. Enables
    data exploration for users with visual impairments through multiple sensory
    modalities. For more details see the 'MAIDR' project
    <https://maidr.ai/>.

Tools for Multilevel Analysis of Individual Heterogeneity and
    Discriminatory Accuracy (MAIHDA) for intersectional inequality research.
    Methods are described in Merlo (2018) <doi:10.1016/j.socscimed.2017.12.026>
    and Evans et al. (2018) <doi:10.1016/j.socscimed.2017.11.011>. The package
    creates intersectional strata, fits multilevel MAIHDA models, estimates
    variance partition coefficients, proportional change in variance, stratum
    effects, and discriminatory-accuracy summaries, and provides diagnostic and
    presentation plots.