Allows users to derive multi-objective weights from pairwise comparisons, which
    research shows is more repeatable, transparent, and intuitive other techniques. These weights
    can be rank existing alternatives or to define a multi-objective utility function for optimization.

This is an accessible template for 'pkgdown'. It uses two
    bootstrap themes, Flatly and Darkly and utilizes the
    'prefers-color-scheme' CSS variable to automatically serve either of
    the two based on user’s operating system setting, or allowing them to
    manually toggle between them.

Design and analyze two-stage randomized trials with a continuous
    outcome measure. The package contains functions to compute the required 
    sample size needed to detect a given preference, treatment, and selection 
    effect; alternatively, the package contains functions that can report the 
    study power given a fixed sample size. Finally, analysis functions are 
    provided to test each effect using either summary data (i.e. means, 
    variances) or raw study data <doi:10.18637/jss.v094.c02>.

Convenient structures for creating, sourcing, reading, writing
  and manipulating ordinal preference data. Methods for writing to/from PrefLib
  formats. See Nicholas Mattei and Toby Walsh "PrefLib: A Library of Preference
  Data" (2013) <doi:10.1007/978-3-642-41575-3_20>.

Generates design matrix for analysing real paired comparisons and derived paired comparison data (Likert type items/ratings or rankings) using a loglinear approach. Fits loglinear Bradley-Terry model (LLBT) exploiting an eliminate feature. Computes pattern models for paired comparisons, rankings, and ratings. Some treatment of missing values (MCAR and MNAR). Fits latent class (mixture) models for paired comparison, rating and ranking patterns using a non-parametric ML approach.

Dynamize headers or R code within 'Rmd' files to prevent proliferation of 'Rmd' files for similar reports. Add in external HTML document within 'rmarkdown' rendered HTML doc.