Performing Item Response Theory analysis such as parameter estimation, ability estimation, item and model fit analyse, local independence assumption, dimensionality assumption, characteristic and information curves under various models with a user friendly 'shiny' interface.

Package including functions and interactive shiny application
    for the psychometric analysis of educational tests, psychological
    assessments, health-related and other types of multi-item
    measurements, or ratings from multiple raters.

An extension to shiny that brings interactions and animation effects from
    'jQuery UI' library.

Perform common useful JavaScript operations in Shiny apps that will
    greatly improve your apps without having to know any JavaScript. Examples
    include: hiding an element, disabling an input, resetting an input back to
    its original value, delaying code execution by a few seconds, and many more
    useful functions for both the end user and the developer. 'shinyjs' can also
    be used to easily call your own custom JavaScript functions from R.

Provides an interactive Kanban board widget for 'shiny' applications. 
    It allows users to manage tasks using a drag-and-drop interface and offers customizable styling options. 
    'shinykanban' is ideal for project management, task tracking, and agile workflows within 'shiny' apps.

An interactive Shiny application to perform fast parameter inference on
    dynamical systems (described by ordinary differential equations) using gradient matching.
    Please see the project page for more details.

A collection of highly configurable, touch-enabled knob input controls for 'shiny'. These components can be styled to fit in perfectly in any app, and allow users to set precise values through many input modalities. Users can touch-and-drag, click-and-drag, scroll their mouse wheel, double click, or use keyboard input.

Web front end for your 'R' functions producing plots or tables.
    If you have a function or set of related functions, you can make them
    available over the internet through a web browser. This is the same
    motivation as the 'shiny' package, but note that the development of
    'shinylight' is not in any way linked to that of 'shiny' (beyond the use of
    the 'httpuv' package). You might prefer 'shinylight' to 'shiny' if you want
    a lighter weight deployment with easier horizontal scaling, or if you want
    to develop your front end yourself in JavaScript and HTML just using
    a lightweight remote procedure call interface to your R code on the
    server.