Implements the Block-wise Rank in Similarity Graph Edge-count 
    test (BRISE), a rank-based two-sample test designed for block-wise 
    missing data. The method constructs (pattern) pair-wise similarity graphs 
    and derives quadratic test statistics with asymptotic chi-square 
    distribution or permutation-based p-values. It provides both 
    vectorized and congregated versions for flexible inference. 
    The methodology is described in Zhang, Liang, Maile, and 
    Zhou (2025) <doi:10.48550/arXiv.2508.17411>.

Functions to combine data on voting blocs' 
    size, turnout, and vote choice to estimate each bloc's
    vote contributions to the Democratic and Republican parties.
    The package also includes functions for uncertainty estimation and
    plotting. Users may define voting blocs along a discrete or continuous variable.
    The package implements methods described in Grimmer, Marble, and Tanigawa-Lau (2023) <doi:10.31235/osf.io/c9fkg>.

Write blog posts and web pages in R Markdown. This package
    supports the static site generator 'Hugo' (<https://gohugo.io>) best,
    and it also supports 'Jekyll' (<https://jekyllrb.com>) and 'Hexo'
    (<https://hexo.io>).

Provides methods for estimating the area under the concentration
    versus time curve (AUC) and its standard error in the presence of Below the
    Limit of Quantification (BLOQ) observations. Two approaches are implemented:
    direct estimation using censored maximum likelihood, and a two-step approach
    that first imputes BLOQ values using various methods and then computes the
    AUC using the imputed data. Technical details are described in Barnett et al.
    (2020), "Methods for Non-Compartmental Pharmacokinetic Analysis With
    Observations Below the Limit of Quantification," Statistics in
    Biopharmaceutical Research. <doi:10.1080/19466315.2019.1701546>.

Tools designed to make it easier for beginner and intermediate users to build and validate 
    binary logistic regression models. Includes bivariate analysis, comprehensive regression output, 
    model fit statistics, variable selection procedures, model validation techniques and a 'shiny' 
    app for interactive model building.