Calculates, via simulation, power and appropriate stopping
  alpha boundaries (and/or futility bounds) for sequential analyses (i.e.,
  group sequential design) as well as for multiple hypotheses (multiple tests
  included in an analysis), given any specified global error rate. This enables
  the sequential use of practically any significance test, as long as the
  underlying data can be simulated in advance to a reasonable approximation.
  Lukács (2022) <doi:10.21105/joss.04643>.

Conduct power analyses and inference of marginal effects. 
    Uses plug-in estimation and influence functions to perform robust inference,
    optionally leveraging historical data to increase precision with
    prognostic covariate adjustment. The methods are described in
    Højbjerre-Frandsen et al. (2025) <doi:10.48550/arXiv.2503.22284>.

A collection of R Markdown templates for creating simple and easy 
  to personalize single page websites.

Free UK geocoding using data from Office for National Statistics.
    It is using several functions to get information about post codes, outward
    codes, reverse geocoding, nearest post codes/outward codes, validation, or
    randomly generate a post code. API wrapper around <https://postcodes.io>.

Generates simple and beautiful one-page HTML reference manuals 
    with package documentation. Math rendering and syntax highlighting are done 
    server-side in R such that no JavaScript libraries are needed in the
    browser, which makes the documentation portable and fast to load.

Provides useful tools for both users and developers of packages 
  for fitting Bayesian models or working with output from Bayesian models. 
  The primary goals of the package are to: 
  (a) Efficiently convert between many different useful formats of
  draws (samples) from posterior or prior distributions.
  (b) Provide consistent methods for operations commonly performed on draws, 
  for example, subsetting, binding, or mutating draws.
  (c) Provide various summaries of draws in convenient formats.
  (d) Provide lightweight implementations of state of the art posterior 
  inference diagnostics. References: Vehtari et al. (2021) 
  <doi:10.1214/20-BA1221>.